SCRO / Journées de l'optimisation

HEC Montréal, 29-31 mai 2023


HEC Montréal, 29 — 31 mai 2023

Horaire Auteurs Mon horaire

MEFII Mathematical Economics and Finance II

30 mai 2023 15h30 – 17h10

Salle: Procter & Gamble (vert)

Présidée par Soodabeh Asadi Dezaki

4 présentations

  • 15h30 - 15h55

    Premarket Termination of Drugs: Alliance Portfolio Optimization and New Drug Development Performance 

    • Hadi Eslami, prés., Saint Mary's University

    The termination rate of a drugs in the new drug development (NDD) process is very high, and FDA reports indicate that only one in every 5,000 compounds will make it to the market. This substantial premarket termination rate has major operations post-market supply chains implications for the healthcare sector, and, yet we know very little as to what leads firms to terminate drugs in premarket stages for reasons apart from medical reasons. In this study, we take the drug as the focal unit of analysis and examine whether/how the termination likelihood of a drug is influenced by characteristics/compositions of its designated alliance portfolio (alliances formed for the development and launch of the drug). Drawing primarily from Transaction Cost Economics theory, we first developed and empirically examined an inverse U-shape association between the termination likelihood of drugs and their associated alliance portfolio size. We also examined the effects of various alliance portfolio compositions on the likelihood of drug termination. Using econometrics models, we examined the termination likelihood of 3,725 drugs accounting for a total of 8,911 alliances formed by 387 focal biopharmaceutical firms to develop these 3,725 drugs. Our findings reveal a curvilinear relationship between the alliance portfolio size and the termination likelihood of drugs. We also found out that broad scope and horizontal type of alliances proportionally enhance the likelihood of drug termination. 

  • 15h55 - 16h20

    Triple Uncertainties: Credence Goods, Deceptive Counterfeits, and Fake Reviews

    • Yongqin Lei, Ivey Business School
    • Hubert Pun, Ivey Business School
    • Fredrik Odegaard, prés., Western University

    Counterfeits have been a persistent issue in online marketplaces. Concerned about product quality, customers frequently rely on external signals, such as product badges that are granted based on product ratings, before purchasing. However, unethical sellers may exploit the badge system by acquiring fake positive reviews. In this paper, we use a game-theoretical model to study a market comprising an authentic seller and a deceptive counterfeiter; they sell credence goods (e.g., nutritional supplements) whose qualities are difficult to evaluate even after consumption. We consider two types of consumers: savvy consumers, who understand that the endorsement badge is product-dependent and not seller-dependent, and novice consumers, who mistakenly think the badge testifies a seller's authenticity. Our results indicate that the authentic seller does not acquire fake reviews in equilibrium, while the counterfeiter may acquire some to mislead customers. Moreover, the number of acquired fake reviews decreases as the fraction of savvy consumers increases, suggesting that online platforms can combat fake reviews by increasing the proportion of savvy customers, for instance, by clearly communicating that badges are product-dependent rather than seller-dependent.

  • 16h20 - 16h45

    Worst-Case Conditional Value at Risk for Asset Liability Management: A Novel Framework for General Loss Functions

    • Alireza Ghahtarani, prés., Dalhousie University
    • Ahmed Saif, Associate Professor at Dalhousie University
    • Ghasemi Alireza, Dalhousie University

    This research presents a new framework to address the challenges of the asset liability manage-
    ment (ALM) problem, which requires accounting for uncertainty in asset returns and the present
    value of liabilities. The proposed approach is based on worst-case conditional value at risk
    (WCVaR) and involves developing a worst-case lower partial moment (WCLPM) and
    WCVaR for the general loss function. Taylor approximation is used to establish the theoretical
    foundation for WCLPM and WCVaR to handle nonlinear/linear loss functions of random
    variables. Additionally, the data-driven moment-based ambiguity set is developed to consider
    uncertainty in the moments of random variables in the ALM problem. The proposed approach is
    evaluated using real-world data from the Canada Pension Plan (CPP) and is shown to outperform
    the WCVaR method with fixed moments and stochastic programming model of the ALM in out-
    of-sample performance. The proposed methodology has the potential to be applied to other fields
    involving nonlinear loss functions with uncertainty to develop WCVaR.

  • 16h45 - 17h10

    Pharmaceutical Competition with Risk-Sharing: A Game-Theoretic Perspective

    • Soodabeh Asadi Dezaki, prés., Ivey Business School, Western University
    • Salar Ghamat, Lazaridis School of Business and Economics, Laurier University
    • Greg Zaric, Ivey Business School, Western University

    We study the use of risk-sharing agreements by pharmaceutical companies to establish market share in an oligopolistic market. We analyze the competition between an incumbent drug manufacturer and a market entrant that may encroach the market using risk-sharing agreements to increase its market coverage. In response to the entry of the new drug the incumbent may also adjust its price or introduce risk-sharing agreements. We find that price reduction by the incumbent can be a better response by the incumbent when there is a cost associated with the implementation of a risk-sharing agreement.

    Keywords: risk-sharing agreement; pharmaceutical prices; game theory