INFORMS 2021 Program Book

INFORMS Anaheim 2021

WB40

WB37 CC Room 210C In Person: Learning and Dynamic Pricing General Session Chair: Rene A Caldentey, The University of Chicago, Chicago, IL, 60637-1656, United States 1 - Incentive Design and Pricing under Limited Inventory Ruiting Zuo, National University of Singapore, Singapore, 138601, Singapore, Jussi Keppo, Tinglong Dai We consider an airline company that sells tickets for its flight. To boost the demand, the company hires a sales agent who exerts unobservable effort over time in response to a dynamic compensation contract offered by the airline company. The company is concerned not only about utilizing its capacity, but also about loss of goodwill when the realized demand exceeds its capacity. We model the company’s dynamic compensation and pricing problem using a continuous- time principal-agent framework. The dynamic strategy depends on the random demand, remaining capacity level, and the time to the departure. Under the estimated model parameters and optimal dynamic pricing, the optimal static compensation scheme provides the airline company with over 99% of the benefits derived from the corresponding optimal dynamic compensation scheme. 2 - Diffusion Approximations for a Class of Sequential Learning Problems Rene A. Caldentey, The University of Chicago, Booth School Of Business, Chicago, IL, 60637-1656, United States, Victor Araman We consider a decision maker who must choose an action in order to maximize a reward function that depends also on an unknown parameter. The decision maker can delay taking the action in order to experiment and gather additional information on the unknown parameter. We model the decision maker’s problem using a Bayesian sequential experimentation framework and use dynamic programming and diffusion-asymptotic analysis to solve it. For that, we scale our problem in a way that both the average number of experiments that is conducted per unit of time is large and the informativeness of each individual experiment is low. Under such regime, we derive a diffusion approximation for the sequential experimentation problem, which provides a number of important insights about the nature of the problem and its solution.” WB40 CC Room 211B In Person: Managing Uncertainty and Scarcity in Energy Systems: Part II General Session Chair: Sebastian Souyris, University of Illinois Urbana-Champaign, Champaign, IL, 61820, United States 1 - Network Effects and Incentives in Solar Panel Diffusion: A Dynamic Discrete Choice Approach Sebastian Souyris, University of Illinois Urbana-Champaign, Urbana, IL, 61801-4860, United States, Anantaram Balakrishnan, Jason Duan, Varun Rai As the price of residential photovoltaic (PV) solar panels and government incentives decline intandem, rendering the net cost relatively flat over the years, the annual new solar capacity hasbeen increasing significantly since 1998. In this paper, we study the PV solar panel market inAustin, Texas. We develop a dynamic discrete choice model that explores the neighborhoodnetwork effects and the results of various incentive policies on the diffusion of PV systems. Wefind the network effects are significant, and unobserved household heterogeneity isconsiderable. We use policy simulations to predict the potential impact of various rebateschedules and optimize rebates according to the policymaker objective.

Wednesday, 9:45AM 10:45AM

Wednesday Plenary 01 CC Ballroom E /Virtual Theater 1 Plenary: Improving Supply Chain Resilience: Looking Back and Looking Forward Plenary Session 1 - Plenary: Improving Supply Chain Resilience: Looking Back and Looking Forward Christopher S. Tang, University of California-Los Angeles, UCLA Anderson School of Management, Operations and, Los Angeles, CA, 90095-1481, United States Prolonged shortages of PPE, vaccines, and semiconductor chips during the Covid- 19 Pandemic exposed the vulnerabilities of global supply chains. In this plenary talk, I share my observations and discuss potential steps that government representatives, industry leaders, and INFORMS members can take to improve supply chain resilience.” WC07 CC Room 303B In Person: Social Media and Online Platforms General Session Chair: Yun Young Hur, Georgia Tech, Atlanta, GA, 30312, United States 1 - Engagement in Interactive Social Media Campaigns: Joint Effects of Social Cause and Monetary Reward Elizabeth Han, Georgia Institute of Technology, Atlanta, GA, United States, Han Zhang, Samuel Bond Interactivesocial media campaigns, which ask consumers to create user-generated contentson behalf of a brand, have been a popular social media marketing strategy. Inthis work, we examine how the two common incentives (social cause; monetaryrewards) influence engagement in these campaigns. Based on theself- determination theory, we propose that incorporating social cause ormonetary rewards in a campaign will increase engagement, but adding both willbe counter- productive due to the crowding-out of the conflicting motivations.Results from two laboratory experiments confirm our hypotheses. Our researchprovides insights on engagement in social media campaigns and contentgeneration. 2 - Netflix or AMC: Predicting Release Strategies in the Age of Options Lavada Blanton, Masters Candidate, Oklahoma State University, Stillwater, OK, United States Given the pandemic, production companies must decide the risks involved in the traditional movie release vs alternatives (e.g., Netflix). This project analyzed 1,605 movies, released through either the traditional movie theater format or through a streaming service since 2010. To compare distribution type, box office success in streaming movies is predicted based on a theatrical release model. Box office revenue is compared between distribution methods to profile movies based on categories such as genre and release month. Key indicators of box office success are evaluated to find the optimal “Movie Mix” based on release strategy. 3 - The Impact of Physical Attractiveness on Donation and Sharing in Medical Crowdfunding: A Large-scale Randomized Field Experiment Yun Young Hur, Georgia Tech, Georgia, Atlanta, GA, 30312, United States This study examines the impact of physical attractiveness on two types of helping behavior: sharing and donation, in the context of medical crowdfunding. We conduct a large-scale randomized field experiment with one of the largest medical crowdfunding platforms in China to discover the beauty penalty for female patients in raising donations and the beauty premium for male patients in sharing medical crowdfunding posts. Neither the penalty for female patients nor the premium for male patients is replicated in the other type of helping behavior. We refer to the impression management theory and explain our findings in relation to people’s tendencies to manage impressions in public and show less restricted behaviors in private. Using two moderators, we affirm that impression management is more salient when a larger audience observes the behavior. Wednesday, 11:00AM-12:20PM

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