INFORMS 2021 Program Book

INFORMS Anaheim 2021

SB03

5 - Downstream Protection Value: Detecting Critical Zones for Effective Fuel-treatment under Wildfire Risk Cristobal Pais, University of California - Berkeley, Berkeley, CA, 94709, United States The destructive potential of wildfires has been exacerbated by climate change, causing their frequencies and intensities to continuously increase globally. Generating fire-resilient landscapes via efficient and calculated fuel-treatment plans is critical to protecting native forests, agricultural resources, biodiversity, and human communities. To tackle this challenge, we propose a framework that integrates fire spread, optimization, and simulation models. We introduce the concept of Downstream Protection Value (DPV), a flexible metric that assays and ranks the impact of treating a unit of the landscape, by modeling a forest as a network and the fire propagation as a tree graph. Using our open-source decision support system, custom performance metrics can be optimized to minimize wildfire losses, obtaining effective treatment plans. Experiments with real forests show that our model is able to consistently outperform alternative methods and accurately detect high-risk and potential ignition areas, focusing the treatment on the most critical zones. Results indicate that our methodology is able to decrease the expected area burned and fire propagation rate by more than half in comparison to alternative methods under ignition and weather uncertainty. Hybrid TIMES Best Working Paper Award Sponsored: Technology, Innovation Management and Entrepreneurship Sponsored Session Chair: Evgeny Kagan, Johns Hopkins University 1 - Product Development in Crowdfunding: Theoretical and Empirical Analysis Sidika Tunc Candogan, University College London, London, E14 5AA, United Kingdom, Philipp Cornelius, Ersin Korpeoglu, Bilal Gokpinar, Christopher Tang Crowdfunding goes beyond raising funds. Entrepreneurs often use crowdfunding to solicit feedback from customers to improve their products. We show, both theoretically and empirically, that as the initial development level increases, the likelihood of product improvement during a campaign at first increases and then decreases. Also, while our theoretical model intuitively predicts that the likelihood of campaign success will always increase with the initial development level, our empirical analysis shows that there is first an increase but then an unexpected decrease. We find that this discrepancy can be explained by feature fatigue, and incorporate this effect into our theoretical model to generate prescriptions. While crowdfunding experts believe that products should be as developed as possible before a campaign, we show that this is not always the best strategy. 2 - Delegated Concept Testing in New Product Development Jochen Schlapp, Frankfurt School of Finance & Management gGmbH, Frankfurt Am Main, 60322, Germany, Gerrit Schumacher 3 - WeStore or AppStore: Customer Behavior Differences in Mobile Apps and Social Commerce Kejia Hu, Vanderbilt University, Nashville, TN, 37215-1710, United States, Nil Karacaoglu 4 - Learning Best Practices: Can Machine Learning Improve Human Decision-Making? Park Sinchaisri, The Wharton School, University of Pennsylvania, Oakland, CA, 94612, United States, Hamsa Bastani, Osbert Bastani Hybrid Academic Job Search Sponsored: Minority Issues Forum Sponsored Session Chair: Zahra Azadi, University of Miami Herbert Business School, Coral Gables, FL, 33158, United States 1 - Academic Job Search Zahra Azadi, University of Miami Herbert Business School, Coral Gables, FL, 33158, United States The purpose of this session is to bring visibility to the students and postdocs looking for academic positions. Panelists from both business and engineering schools will share their experiences. This panel discusses the academic interview process and do’s and don’ts associated with the job search. SB04 CC Ballroom D / Virtual Theater 4 SB05 CC Ballroom E / Virtual Theater 5

SB03 CC Ballroom C / Virtual Theater 3 Hybrid ENRE Award Session Sponsored: Energy, Natural Resources and the Environment Sponsored Session Chair: Benjamin D. Leibowicz, University of Texas-Austin, Austin, TX, 78712-1591, United States 1 - Uncertain Bidding Zone Configurations: The Role of Expectations for Transmission and Generation Capacity Expansion Harry van der Weijde, Friedrich-Alexander-Universität, Erlangen- Nürnberg, Germany, Mirjam Ambrosius, Jonas Egerer, Veronika Grimm Ongoing policy discussions on the reconfiguration of bidding zones in European electricity markets induce uncertainty about the future market design. This paper analyzes how this uncertainty affects market participants and their long-run investment decisions. We propose a stochastic multilevel model which includes uncertainty about the future bidding zone configuration. If potential future bidding zone configurations provide improved regional price signals, welfare gains materialize even if the change does not actually take place. As a consequence, welfare gains of an actual change of the bidding zone configuration are substantially lower due to those anticipatory effects. 2 - Promoting Solar Panel Investments: Feed-in-tariff versus Tax-rebate Policies Safak Yucel, Georgetown University, Washington, DC, 20057, United States We analyze the government’s preference between feed-in-tariff and tax-rebate policies to promote households’ solar panel investments in the presence of household heterogeneity with respect to generating efficiency, electricity price variability and investment cost variability. This paper has received the 2021 Best Publication Award in Environment and Sustainability from the INFORMS Section on Energy, Natural Resources and the Environment. 3 - Load Restoration in Islanded Microgrids: Formulation and Solution Strategies Shourya Bose, University of California, Santa Cruz, CA, United States, Yu Zhang Extreme weather events induced by climate change can cause significant disruptions to the normal operation of electric distribution systems (DS), including isolation of parts of the DS due to damaged transmission equipment. In this paper, we consider the problem of load restoration in a microgrid (MG) that is islanded from the upstream DS because of an extreme weather event. The MG contains sources of distributed generation such as microturbines and renewable energy sources, in addition to energy storage systems. We formulate the load restoration task as a non-convex optimization problem with complementarity constraints. We propose a convex relaxation of the problem that can be solved via model predictive control. In addition, we propose a data-driven policy-learning method called constrained policy optimization. The solutions from both methods are compared by evaluating their performance inload restoration, which is tested on a 12-bus MG. 4 - Impact of Carbon Pricing Policies on the Cost and Emission of the Biomass Supply Chain: Optimization Models and a Case Study Taraneh Sowlati, University of British Columbia, Vancouver, BC, V6 T. 1Z4, Canada Carbon tax, carbon cap-and-trade, and carbon offset are the main carbon pricing policies in practice. Several studies analyzed the impacts of these policies on optimum solutions of biomass supply chain models. However, due to the focus on specific case studies, insights from these studies may not be general. In this paper, the impact of carbon pricing policies on the optimum solutions of case- independent biomass supply chain models is studied. Several propositions that discuss the impact of carbon pricing policies on optimum cost and emissions of biomass supply chain models are presented and proved mathematically. Next, mathematical models are developed to determine the optimal feedstock mix of a biomass-fed district heating plant. The case study results are used to numerically confirm all propositions. When the carbon price increases, the models prescribe the replacement of natural gas with biomass. Carbon tax and carbon cap-and- trade models result inequal optimum decision variables and emissions for equal carbon prices. The carbon cap-and-trade model has less cost than the carbon tax model if the carbon price is more than the price of initial allowance. Careful allotment of the compliance target is important for the carbon offset model because it bounds the optimum emissions.

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