INFORMS 2021 Program Book

INFORMS Anaheim 2021

MC13

goes bankrupt and transfers all of its wealth to the supplier. We consider three treatments varying degree of bankruptcy risk. Preliminary results show that human retailers with high risk significantly understock while retailers with low risk slightly overstock. 2 - A Theoretical and Experimental Investigation into the Welfare Consequences of Late Payments Kyle Hyndman, University of Texas at Dallas, Richardson, TX, 75080-3021, United States, Matthew Walker We analyse how late payments affect market entry and price competition. Buyers first send a signal to potential suppliers about their intended payment date. Suppliers then decide whether to incur a fixed and irreversible cost to enter into price competition. After the seller and winning bid is determined, the buyer chooses the ex-post payment date, which may or may not coincide with the ex- ante date promised. We show that in theory, if firms value payment made or received late below its nominal value, payment delays feed into higher consumer prices and reduced competition. Reneging on a promise to pay on-time entails a cost for the buyer. If this cost is not set carefully, a welfare loss arises. We find support for the main predictions of the model in an experiment. 3 - Sourcing Mechanisms for a Single Product under Unstructured Bargaining Haokun Du, University of Texas at Dallas, Richardson, TX, United States, Bin Hu, Elena Katok Product sourcing is critical in operations and has attracted great attention. In this paper, we consider unstructured bargaining between suppliers and retailer for a single product. Using “Nash-in-Nash” solution, we have found that the procurement cost decreases with the number of suppliers under simultaneous sourcing mechanism. Sequential sourcing mechanism has also been considered. Minimized cost under this mechanism will award all desired quantities to the first supplier, leaving the other supplier(s) as a mere threat. This suggests that the information update that we are hypothesizing will never occur in equilibrium. We have also shown which mechanism leads to cheaper cost of procurement under a simpler setting theoretically. Experiments are proposed to test the theory. MC13 CC Room 201A In Person: Simulation Contributed Session Chair: Patrick Deenen, University of Technology-Eindhoven, Eindhoven, 5623CH, Netherlands 1 - Optimal Control Models of a Biological Invader using Gaussian Kernels Sevilay Onal, University of Illinois Springfield, Springfiled, IL, United States, Sabah Bushaj, Esra Buyuktahtakin Toy, Jennifer Smith, Gregory Houseman Weeds have been detrimental to the crop acreage and yield. Sericea lespedeza is recognized as a biological invader in the Federal Noxious Weed Act in 2000. Control programs to such infestation have been designed to reduce the harmful impacts on biodiversity and bioeconomy in the Great Plains of the U.S. An integrated simulation-optimization model estimates the seed dispersal using Gaussian cell-to-cell transition probabilities, and the treatment locations are prescribed over a predetermined time period depending on the infestation level. 2 - Simulation-based Optimization for Convex Functions over Discrete Sets Eunji Lim, Adelphi University, Garden City, NY, United States We propose a new iterative algorithm for finding a minimum point of a real- valued function f* with the domain X, when f* is known to be convex, but only noisy observations of f*(x) are available at each point x in X. The proposed algorithm not only estimates the minimum point of f*, but also provides the probability of each point in X being a minimum point of f*, using the fact that f* is convex. Numerical results indicate that the proposed algorithm converges to a minimum point of f* as the number of iterations increases and shows fast convergence especially in the early stage of the iterations. 3 - Consumer Rental Intentions for Electric Vehicles: Are Green Consumers Quality-conscious or Price-conscious? Adeela Gulzari, University of North Texas, Denton, TX, United States, Yuchen Wang, Victor R. Prybutok Research has demonstrated that green consumers who have a positive attitude towards environmental protection are inclined to purchase an eco-friendly car such as an Electric Vehicle (EV). However, individuals who are interested in using an EV without purchase intention can also be concerned about the environment. Renting a car is a low-involvement decision and explores a different dimension of a consumer’s thought process. In this research, we study consumer rental intentions for EVs and evaluate whether price or quality-related constructs significantly affect rental intentions using a covariance-based structural equation model.

MC11 CC Room 304C In Person: Economics and Computation II Award Session Chair: Ignacio Rios, University of Texas at Dallas, Richardson, TX, 75080, United States Co-Chair: Shipra Agrawal, Columbia University, New York, NY, 10027- 6623, United States 1 - Robustly-optimal Mechanism for Selling Multiple Goods Weijie Zhong, Stanford University, Stanford, CA, United States, Yeon-Koo Che We study robustly-optimal mechanisms for selling multiple items. The seller maximizes revenue against a worst-case distribution of a buyer’s valuations within a set of distributions, called an “ambiguity” set. We identify the exact forms of robustly optimal selling mechanisms and the worst-case distributions when the ambiguity set satisfies a variety of moment conditions on the values of subsets of goods. We also identify general properties of the ambiguity set that lead to the robust optimality of partial bundling which includes separate sales and pure bundling as special cases. 2 - Equilibrium Computation of Generalized Nash Games: A New Lagrangian-Based Approach Jong Gwang Kim, Purdue University, West Lafayette, IN, United States This paper presents a primal-dual method, based on a new form of Lagrangian, for computing an equilibrium of generalized Nash game (GNEP) where each player’s feasible strategy set depends on the other players’ strategies. We establish the equivalence between a saddle point of the Lagrangian and an equilibrium of the GNEP. We then propose a simple algorithm that is globally convergent to the saddle point. Our method has novel features over existing approaches; it does not require any boundedness assumptions and is the first design of an algorithm to solve general GNEPs in a distributed manner. Numerical experiments are performed on test problems to demonstrate the effectiveness of the proposed method. 3 - Improving Match Rates in Dating Markets Through Assortment Optimization Ignacio Rios, University of Texas at Dallas, Richardson, TX, United States, Daniela Saban, Fanyin Zheng We study how a dating platform should dynamically select the profiles to show to each user in each period to maximize the expected number of matches in a time horizon. We model the platform’s problem as a dynamic optimization problem, and we use econometric tools to estimate the inputs of our model using our partner’s data. We find that the number of matches obtained in the recent past has a negative effect on the like behavior of users. Leveraging our data findings, we propose heuristics to solve the platform’s problem. Through simulations and a field experiment, we show that the proposed algorithms can substantially improve the number of matches generated by the platform. 4 - Online Learning via Offline Greedy Algorithms: Applications in Market Design and Optimization Rad Niazadeh, Chicago Booth School of Business, Chicago, IL, United States, Negin Golrezaei, Fransisca Susan, Joshua Wang, Ashwinkumar Badanidiyuru Motivated by online decision-making in time-varying combinatorial environments, we study the problem of transforming offline algorithms to their online counterparts. We focus on offline combinatorial problems that are amenable to a constant factor approximation using a greedy algorithm that is robust to local errors. For such problems, we provide a general framework that efficiently transforms offline robust greedy algorithms to online ones using Blackwell approachability. Demonstrating the flexibility of our framework, we apply our offline-to-online transformation to several problems at the intersection of revenue management, market design, and online optimization. MC12 CC Room 304D In Person: Supply Chain Payments and Financing General Session Chair: Kyle Hyndman, University of Texas at Dallas, Richardson, TX, 75080-3021, United States 1 - An Experimental Investigation of Supplier Financing Rihuan Huang, Cornell University, Ithaca, NY, 14853-6900, xvUnited States, Andrew M. Davis, Kyle Hyndman We behaviorally study the newsvendor setting with capital constraint and supplier financing. In our setting, a retailer with some initial wealth orders from a supplier who sets a wholesale price, and will pay the supplier after demand realization if the initial wealth is insufficient. If demand is too low, the retailer

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