About

Vibhanshu Abhishek is an Associate Professor of Information Systems at the Paul Merage School of Business, University of California - Irvine. His research focuses on the effect of emerging technologies on consumers' behavior, business strategy, and market structure. He is particularly interested in multi-channel coordination and examines issues in multi-channel retail, advertising, and pricing. His work studies how consumers respond to different forms of advertising and how companies can strategically utilize new advertising channels to connect with their consumers. Additionally, he investigates the dynamics of e-commerce marketplaces and their interaction with traditional retail, as well as consumer behavior in shared urban mobility systems. Dr. Abhishek holds a PhD in Operations and Information Management and an M.A. in Statistics from the Wharton School, University of Pennsylvania, and a B.Tech in Computer Science from IIT Kanpur. Before joining UC Irvine, he was an Assistant Professor of Information Systems at the Heinz College, Carnegie Mellon University. His research has been published in top management journals and has been cited in various popular press outlets. He has received numerous awards and grants for his research and teaching, and has collaborated with several firms including McKinsey & Co., Sequoia Capital, LEGO, Adobe, IBM, and Omnicom. His expertise encompasses technology-enabled markets, digital advertising, retail, online platforms, machine learning, and causal inference.

Research topics

• Computer Science
• Economics
• Artificial Intelligence
• Microeconomics
• Business
• Marketing
• Telecommunications
• Commerce
• Industrial organization
• Psychology

Selected publications

• Generative AI Adoption by Creator Platforms 

  SSRN Electronic Journal · 2025-01-01 · 1 citations

  articleOpen access
  PublisherDOI

• Do Sellers Benefit from Sponsored Product Listings? Evidence from an Online Marketplace

  Marketing Science · 2024-03-19 · 7 citations

  articleSenior author

  This paper shows that consumers prefer organic listings in the top-ranked positions to sponsored listings of the same product/position in an online marketplace.

  PublisherDOI

• The Impact of “Retail Media” on Online Marketplaces: Insights from a Field Experiment

  Information Systems Research · 2024-05-15 · 9 citations

  article1st authorCorresponding

  A part of retail media wherein sponsored product listings are interleaved with organic product listings in the search results is a large and growing phenomenon. In this paper, we study the impact of displaying sponsored listings at top positions for the platform. Analyzing data from a large-scale field experiment at a leading online marketplace in India, we find nuanced results that substantially vary across product categories. In the electronics category, the sponsored listings receive fewer clicks than the organic listings that they replace. Surprisingly, this effect is reversed in the clothing category, in which the ads perform better than the displaced organic listings, suggesting that sponsored listings might help the platform identify new high-relevance products and improve search rankings for these categories. At the search level, we find that increasing the fraction of sponsored listings (by about 10% points) in the search results does not affect the performance in any product category. This implies that ads bring in additional revenue for the marketplace yet do not hurt overall consumer response (in the short run). We theorize that the variation across categories occurs because of differing degrees of information asymmetry on product relevance between the marketplace and the sellers.

  PublisherDOI

• Bias in Generative AI

  arXiv (Cornell University) · 2024 · 28 citations

  • Computer Science
  • Artificial Intelligence
  • Computer Science

  This study analyzed images generated by three popular generative artificial intelligence (AI) tools - Midjourney, Stable Diffusion, and DALLE 2 - representing various occupations to investigate potential bias in AI generators. Our analysis revealed two overarching areas of concern in these AI generators, including (1) systematic gender and racial biases, and (2) subtle biases in facial expressions and appearances. Firstly, we found that all three AI generators exhibited bias against women and African Americans. Moreover, we found that the evident gender and racial biases uncovered in our analysis were even more pronounced than the status quo when compared to labor force statistics or Google images, intensifying the harmful biases we are actively striving to rectify in our society. Secondly, our study uncovered more nuanced prejudices in the portrayal of emotions and appearances. For example, women were depicted as younger with more smiles and happiness, while men were depicted as older with more neutral expressions and anger, posing a risk that generative AI models may unintentionally depict women as more submissive and less competent than men. Such nuanced biases, by their less overt nature, might be more problematic as they can permeate perceptions unconsciously and may be more difficult to rectify. Although the extent of bias varied depending on the model, the direction of bias remained consistent in both commercial and open-source AI generators. As these tools become commonplace, our study highlights the urgency to identify and mitigate various biases in generative AI, reinforcing the commitment to ensuring that AI technologies benefit all of humanity for a more inclusive future.

  PublisherOA PDFDOI

• Linking Clicks to Bricks: Understanding the Effects of Email Advertising on Multichannel Sales

  Information Systems Research · 2024-03-25 · 3 citations

  article

  Businesses have widely used email ads to directly send promotional information to consumers. Whereas email ads serve as a convenient tool that allows firms to target consumers online, there is little evidence of their multichannel impact on consumer spending in both online and brick-and-mortar stores. In this paper, we utilize a unique high-dimensional data set from one of the world’s largest office supplies retailers to link each consumer’s online behaviors to item-level purchase records in physical stores. We employ a doubly robust estimator that incorporates nonparametric machine learning methods for causal estimation of observational data. Our results show that email ads significantly increase the retailer’s sales across different channels. We also investigate the effects of email ads on diverse consumer behaviors along the purchase funnel and find that increased sales result from increased purchase probability and a wider variety of products purchased by consumers. Further, we examine several moderating factors, such as product types and consumer segments, that influence the multichannel effects of email advertising. Our study provides empirical evidence for the economic impact of email ads on consumer behavior across different channels and the underlying mechanisms thereof, offering direct implications for multichannel retailers seeking to improve their digital marketing strategies.

  PublisherDOI

• Seller Incentives in Sponsored Product Listings on Online Marketplaces

  SSRN Electronic Journal · 2021-01-01 · 4 citations

  articleOpen accessSenior author
  PublisherDOI

• Business Models in the Sharing Economy: Manufacturing Durable Goods in the Presence of Peer-to-Peer Rental Markets

  Information Systems Research · 2021 · 83 citations

  1st authorCorresponding
  • Business
  • Marketing
  • Commerce

  With peer-to-peer sharing of durable goods like cars, boats, and condominiums, it is unclear how manufacturers should react. They could seek to encourage these markets or compete against them by offering their own rentals. This work shows why the best business model depends on whether consumer usage rates vary or not. Contrary to what might be expected, this paper shows that manufacturers have an incentive to facilitate transactions of P2P rental markets in a large variety of cases. We find that when consumer variation in usage rates is intermediate, the manufacturer is surprisingly best off avoiding offering its own direct rentals option and instead, facilitating a peer-to-peer rental market where consumers can share among themselves. The reason for this is an effect unique to the sharing economy, the equalizing effect. The equalizing effect shows that peer-to-peer rentals uniquely make previously heterogeneous willingness-to-pay among consumers more similar, making it easier for the firm to discriminate between the higher- and lower-value consumers, thus allowing it to extract a higher portion of consumers’ surplus. Surprisingly, there are some cases where peer-to-peer rentals benefit the manufacturer, but consumers are hurt overall (though the lower-usage consumers do always benefit from the availability of peer-to-peer rentals).

  PublisherDOI

• Strategic Timing and Dynamic Pricing for Online Resource Allocation

  Management Science · 2021-01-21 · 21 citations

  articleOpen access1st authorCorresponding

  This paper optimizes dynamic pricing and real-time resource allocation policies for a platform facing nontransferable capacity, stochastic demand-capacity imbalances, and strategic customers with heterogenous price and time sensitivities. We characterize the optimal mechanism, which specifies a dynamic menu of prices and allocations. Service timing and pricing are used strategically to: (i) dynamically manage demand-capacity imbalances, and (ii) provide discriminated service levels. The balance between these two objectives depends on customer heterogeneity and customers’ time sensitivities. The optimal policy may feature strategic idlenexss (deliberately rejecting incoming requests for discrimination), late service prioritization (clearing the queue of delayed customers), and deliberate late-service rejection (focusing on incoming demand by rationing capacity for delayed customers). Surprisingly, the price charged to time-sensitive customers is not increasing with demand—high demand may trigger lower prices. By dynamically adjusting a menu of prices and service levels, the optimal mechanism increases profits significantly, as compared with dynamic pricing and static screening benchmarks. We also suggest a less information-intensive mechanism that is history-independent but fine-tunes the menu with incoming demand; this easier-to-implement mechanism yields close-to-optimal outcomes. This paper was accepted by Gabriel Weintraub, revenue management and market analytics.

  PublisherOA PDFDOI

• Comparative Study Between Taxi and Uber Platforms in the Deployment of Electric Vehicles

  Scholarworks@UNIST (Ulsan National Institute of Science and Technology) · 2020-12-31

  articleSenior author

  Uber-like platforms provide important opportunities to leverage idle vehicle capacity to meet urban mobility needs and reduce the costs of urban transportation. Most existing systems have relied on gasoline and diesel vehicles. At the same time, the development of electric vehicles has created opportunities to lower operating costs and reduce greenhouse gas emissions from urban transportation. In this talk we present two mathematical models for traditional taxi and emerging Uber platforms, respectively, to derive the closed-form solutions that maximize the respective platform???s operating profit. Given that electric vehicles are cheaper to operate but more expensive to acquire than gasoline vehicles, sensitivity analysis is also performed to find out which fuel type vehicle is more suitable for each platform under various vehicle setting scenarios.

  Publisher

• When the Bank Comes to You: Branch Network and Customer Omnichannel Banking Behavior

  Information Systems Research · 2020 · 57 citations

  • Computer Science
  • Business
  • Marketing

  Banks today have been increasingly reducing their physical presence and redirecting customers to digital channels, and yet, the consequences of this strategy are not well studied. This research investigates the effects of banks’ branch network changes (i.e., branch openings and branch closures) on customer omnichannel banking behavior. Using a proprietary data set from a large commercial bank in the United States, this paper shows the asymmetric effects of branch openings and branch closures on customer omnichannel banking behavior. In particular, it finds that branch openings increase customers’ branch transactions. However, the first branch opening leads to a migration of complex transactions to the branches, which might result in a net decrease in online banking in the short term. As consumers interact more with the physical channel, there is a gradual synergistic increase in customers’ transactions via online banking as well as alternative channels due to a learning spillover effect. This learning spillover effect goes from easy online inquiries to more complex online transactions as additional branches open. On the contrary, branch closures result in a favorable migration pattern from the branch channel to online banking. This pattern, however, could be reversed once the last branch closes within the customer’s residential neighborhood.

  PublisherDOI

Frequent coauthors

• Beibei Li

  10 shared

• Kartik Hosanagar

  9 shared

• Kinshuk Jerath

  6 shared

• Peter S. Fader

  5 shared

• Jiaqi Shi

  Qilu Hospital of Shandong University

  5 shared

• Mi Zhou

  University of British Columbia

  4 shared

• Ee‐Peng Lim

  Singapore Management University

  4 shared

• Xueming Luo

  Temple University

  4 shared

Awards & honors

• Excellence in Teaching Award, Paul Merage School of Business…
• MSI Young Scholar, Class of 2019
• Winner, NABE Tech Economics Conference, Poster Competition,…
• Best Paper Award, DH, 2018
• Mobility 21 Research Grant, 2017