Gerry Tsoukalas

Gerry Tsoukalas
  • Senior Fellow

Contact Information

  • office Address:

    3730 Walnut Street
    567 Jon M. Huntsman Hall
    Philadelphia, PA 19104

Research Interests: technology management, platform design

Links: Personal Website

Overview

Gerry Tsoukalas is a Senior Fellow of the Wharton School at the University of Pennsylvania, where he teaches the Wharton MBA core in Business Analytics. He is also Associate Professor at Boston University, and a Fellow of the Luohan Academy.

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Research

  • Jingxing (Rowena) Gan, Noah Gans, Gerry Tsoukalas (Under Revision), Overbooking with Bumping-Sensitive Demand. Abstract

    Overbooking can help service providers improve revenues, but it comes with costs, such as the compensation paid to “bumped” customers. The existing operations management (OM) literature focused on booking limits implicitly assumes that, given pre-defined price
    and bumping compensation, those booking limits do not affect customer demand. Empirical research in marketing however, suggests that bumping negatively affects demand, an important effect that is the focus of this paper.  With airlines as a backdrop, we formulate a model in which a service provider jointly determines price, booking limit, and bumping compensation, and customer reactions to the three induce an equilibrium demand distribution. For the traditional setting in which price and bumping compensation are exogenously fixed, we provide sufficient conditions under which bumping sensitivity leads the airline to reduce overbooking. These conditions suggest that airlines can decouple the value customers obtain from flying from their cost of being bumped.  We demonstrate that effective overbooking policies must nevertheless jointly determine bumping compensation and booking limits. We then consider auction-based compensation schemes and show that, for the airline, they dominate fixed-compensation schemes. Numerical experiments demonstrate that: the equilibrium bumping rates obtained from our model are consistent with those observed in practice; fixed-compensation policies that account for bumping-sensitive demand can significantly outperform those that do not; and auction-based policies can bring smaller but still significant additional gains over those provided by fixed-compensation schemes.  Our results support the empirical observation that bumping negatively affects customer demand and should be carefully managed, and they suggest that, contrary to traditional booking-limit controls, effective overbooking policies must jointly determine booking limits and bumping compensation. Finally, they demonstrate that recently adopted auction-based compensation schemes are a particularly effective means of managing bumping-sensitive demand.

  • Gérard Cachon, Tolga Dizdarer, Gerry Tsoukalas (Working), Pricing Control and Regulation on Online Service Platforms. Abstract

    Online service platforms enable customers to connect with a large population of independent servers and operate successfully in many sectors, including transportation, lodging, and delivery, among others. We study how prices are chosen and fees are collected on the platform. The platform could assert full control over pricing despite being unaware of the servers’ costs (e.g., ride sharing). Or the platform could allow unfettered price competition among the servers (e.g., lodging). This choice influences both the amount of supply available and the overall attractiveness of the platform to consumers. When the platform collects revenue via a commission or a per-unit fee, neither price delegation strategy dominates the other. However, the platform’s best payment structure is simple and easy to implement – it is merely the combination of a commission and a per-unit fee (which can be negative, as in a subsidy). Furthermore, this combination enables the delegation of price control to the servers, which may assist in the classification of the servers as contractors rather than employees. A similar approach can be used to maximize profits by fully disintermediated platforms (i.e., no central owner), such as those enabled by blockchain technology.

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  • Alon Benhaim, Brett H. Falk, Gerry Tsoukalas (Work In Progress), Scaling Blockchains: Can Elected Committees Help?. Abstract

    In the high-stakes race to develop more scalable blockchains, some platforms (Cosmos, EOS, TRON, etc.) have adopted committee-based consensus protocols, whereby the blockchain’s record-keeping rights are entrusted to a committee of elected block producers. In theory, the smaller the committee, the faster the blockchain can reach consensus and the more it can scale. What’s less clear, is whether this mechanism ensures that honest committees can be consistently elected, given voters typically have limited information. Using EOS’ Delegated Proof of Stake (DPoS) protocol as a backdrop, we show that identifying the optimal voting strategy is complex and practically out of reach. We empirically characterize some simpler (suboptimal) voting strategies that token holders resort to in practice and show that these nonetheless converge to optimality, exponentially quickly. This yields efficiency gains over other PoS protocols that rely on randomized block producer selection. Our results suggest that (elected) committee-based consensus, as implemented in DPoS, can be robust and efficient, despite its complexity.

  • Jingxing (Rowena) Gan, Gerry Tsoukalas, Serguei Netessine (Under Review), Financing Platforms with Cryptocurrency: Token Retention, Sales Commission, and ICO Caps. Abstract

    Centralized platforms (e.g., Uber) rely primarily on sales commission (aka, service fees) to generate revenues whereas decentralized blockchain-based startups (e.g., Filecoin) often forego these in favor of token retention. We show that both levers help to overcome moral hazard and incentivize platform building, but they aren’t perfect substitutes and imply a strategic trade-off: the commission approach generally leads to higher long-term profits for the platform founders, whereas token retention can lead to higher service levels, benefiting the service providers and users. Furthermore, the two levers also require different ICO designs when raising capital: commission works best when paired with uncapped ICOs (i.e., unlimited token supply) whereas token retention works best with capped ICOs under certain conditions. These findings offer some guidance and explanations for the operating and ICO design choices of decentralized platforms.

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  • Vlad Babich, Simone Marinesi, Gerry Tsoukalas (2020), Does Crowdfunding Benefit Entrepreneurs and Venture Capital Investors?, M&SOM. Abstract

    We study how a new form of entrepreneurial finance – crowdfunding – interacts with more traditional financing sources, such as venture capital (VC) and bank financing. We model a multi-stage bargaining game, with a moral-hazard problem between entrepreneurs and banks, and a double-sided moral-hazard problem between entrepreneurs and VCs. We decompose the economic value of crowdfunding into cash gains or losses, costs of bad investments avoided, and project-payoff probability update. This economic value is generally shared between entrepreneurs and VC investors, benefiting both. In addition, crowdfunding can alleviate the under-investment problem due to moral-hazard frictions. Furthermore, crowdfunding allows some projects to gain access to both VC and bank financing and the competition between those investor classes benefits entrepreneurs. However, competition from other investors reduces value to VC investors, who may walk away from the deal entirely. This can also hurt entrepreneurs who lose out on valuable VC expertise.

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  • Jingxing (Rowena) Gan, Gerry Tsoukalas, Serguei Netessine (2020), Initial Coin Offerings, Speculation, and Asset Tokenization, Management Science, forthcoming. Abstract

    Initial Coin Offerings (ICOs) are an emerging form of fundraising for Blockchain-based startups. We examine how ICOs can be leveraged in the context of asset tokenization, whereby
    firms issue tokens backed by future assets (i.e., inventory) to finance growth. We (i) make suggestions on how to design such \asset-backed” ICOs—including optimal token
    floating and pricing for both utility and equity tokens (aka, Security Token Offerings, STOs)—taking into account moral hazard (cash diversion), product characteristics and customer demand uncertainty, (ii) make predictions on ICO success/failure, and (iii) discuss implications on rm operating strategy. We show that in unregulated environments, ICOs can lead to significant agency costs, underproduction, and loss of rm value. These inefficiencies, however, fade as product margins and demand characteristics (mean/variance) improve, and are less severe under equity (rather than utility) token issuance. Importantly, the advantage of equity tokens stems from their inherent ability to better align incentives, and thus continues to hold even absent regulation.

    Description
    2019 INFORMS Section on Finance Best Student Paper Award Honorable Mention
  • Brett H. Falk and Gerry Tsoukalas, Inference in Networks with Limited Information.
  • Marcella Hastings, Brett Hemenway, Gerry Tsoukalas (Working), Privacy-preserving Network Analytics. Abstract

    Using financial networks as a backdrop, we develop a new framework for privacy-preserving network analytics. Adopting the debt and equity models of Eisenberg and Noe (2001) and Elliott et al. (2014) as proof of concept, we show how aggregate-level statistics required for stress testing and stability assessment can be derived on real network data, without any individual node revealing its private information to any third party, be it other nodes in the network, or even a central agent. Our work helps bridge the gap between the theoretical models of financial networks that assume agents have full information, and the real world, where information sharing is hindered by privacy and security concerns.

  • Elena Belavina, Simone Marinesi, Gerry Tsoukalas (2020), Rethinking Crowdfunding Platform Design: Mechanisms to Deter Misconduct and Improve Efficiency, Management Science. Abstract

    Lacking credible rule enforcement mechanisms to punish entrepreneurial misconduct, existing reward-based crowdfunding platforms can leave campaign backers exposed to two sources of risk: the risk that entrepreneurs run away with backers’ money (funds misappropriation) and the risk of product misrepresentation (performance opacity). In contrast to prior work, which has mainly focused on studying the first, we examine the adverse consequences of both. We show that not only do both risks have a material impact on crowdfunding efficiency, but they cannot even be analyzed in isolation: rather, their joint presence leads to complex interactions that either dampen or amplify their individual adverse effects. In light of these results, we find that a simple deferred payment scheme with escrow, which the literature argues to be optimal, cannot overcome both sources of friction. We then propose two new designs that Pareto dominate this benchmark. The first design does not rely on escrow, and thus requires less involvement on the part of the platform—but cannot achieve optimality. The second design can restore full efficiency, but requires the platform to take a more active role: we thus provide guidance on how to ease its practical implementation.

    Related
    Links
  • Vlad Babich, Simone Marinesi, Gerry Tsoukalas, Updating the Crowdfunding Narrative in Wharton Public Policy Initiative, 7(5).
  • All Research from Gerry Tsoukalas »

Teaching

Past Courses

  • OIDD3530 - Math Mdlng Appl in Fnce

    Quantitative methods have become fundamental tools in the analysis and planning of financial operations. There are many reasons for this development: the emergence of a whole range of new complex financial instruments, innovations in securitization, the increased globalization of the financial markets, the proliferation of information technology and the rise of high-frequency traders, etc. In this course, models for hedging, asset allocation, and multi-period portfolio planning are developed, implemented, and tested. In addition, pricing models for options, bonds, mortgage-backed securities, and other derivatives are studied. The models typically require the tools of statistics, optimization, and/or simulation, and they are implemented in spreadsheets or a high-level modeling environment, MATLAB. This course is quantitative and will require extensive computer use. The course is intended for students who have strong interest in finance. The objective is to provide students the necessary practical tools they will require should they choose to join the financial services industry, particularly in roles such as: derivatives, quantitative trading, portfolio management, structuring, financial engineering, risk management, etc. Prospective students should be comfortable with quantitative methods such as basic statistics and the methodologies (mathematical programming and simulation) in OIDD6120 Business Analytics and OIDD3210 Management Science (or equivalent). Students should seek permission from the instructor if the background requirements are not met.

  • OIDD6120 - Business Analytics

    "Managing the Productive Core: Business Analytics" is a course on business analytics tools and their application to management problems. Its main topics are optimization, decision making under uncertainty, and simulation. The emphasis is on business analytics tools that are widely used in diverse industries and functional areas, including operations, finance, accounting, and marketing.

  • OIDD6530 - Math Mdlng Appl in Fnce

    Quantitative methods have become fundamental tools in the analysis and planning of financial operations. There are many reasons for this development: the emergence of a whole range of new complex financial instruments, innovations in securitization, the increased globalization of the financial markets, the proliferation of information technology and the rise of high-frequency traders, etc. In this course, models for hedging, asset allocation, and multi-period portfolio planning are developed, implemented, and tested. In addition, pricing models for options, bonds, mortgage-backed securities, and other derivatives are studied. The models typically require the tools of statistics, optimization, and/or simulation, and they are implemented in spreadsheets or a high-level modeling environment, MATLAB. This course is quantitative and will require extensive computer use. The course is intended for students who have strong interest in finance. The objective is to provide students the necessary practical tools they will require should they choose to join the financial services industry, particularly in roles such as: derivatives, quantitative trading, portfolio management, structuring, financial engineering, risk management, etc. Prospective students should be comfortable with quantitative methods, such as basic statistics and the methodologies (mathematical programming and simulation) taught in OIDD 612 Business Analytics or OIDD 321 Management Science (or equivalent). Students should seek permission from the instructor if the background requirements are not met.

Awards And Honors

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Activity

Latest Research

Jingxing (Rowena) Gan, Noah Gans, Gerry Tsoukalas (Under Revision), Overbooking with Bumping-Sensitive Demand.
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Overwhelmed by Too Many Choices When Shopping? Wharton Retail Expert Weighs In

Wharton retail expert discusses why shoppers may feel overwhelmed when faced with many options.…Read More

Knowledge @ Wharton - 2024/12/19
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Awards and Honors

2020 Wharton Teaching Excellence award 2020
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