Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

TA18

2 - Understanding the Value of Overlapping Time Windows for Scheduled Delivery Problems Yeqing Zhou, Columbia University, 550 W. 120th St, New York, NY, 10027, United States, Adam Elmachtoub We consider a problem where customers choose a delivery time window for a service (such as groceries, laundry, or repair) among a set of options that include small and large time windows. A customer who chooses a large time window receives a reward, while the service provider gains some flexibility. Customers arrive dynamically to the system, and the service provider may dynamically price the time windows. We assume a VRP is solved to satisfy all customers at the end of the horizon. We report on the structure of optimal policies as well as the value of various strategies for designing time windows. 3 - Customer Learning for Online Sales of Durable Goods Clark C. Pixton, Assistant Professor, Brigham Young University, 407 N. 2150 W, Provo, UT, 84601, United States Motivated by data from a large online retailer, we study online sales of durable goods, focusing on the effects of uncertainty about product quality and learning from customer reviews. We describe the nature of the tradeoff between learning product quality over time and substitution effects between products offered in the same category on the same website. We offer an alternate explanation for market dominance based on transient effects of a learning process which involves decisions under risk, and show that the learning is slower and market dominance more likely in higher price markets. We discuss operational implications for new product timing and incentivizing customer reviews. n TA16 North Bldg 127B Operations in Developing Economies Sponsored: Manufacturing & Service Oper Mgmt/Sustainable Operations Sponsored Session Chair: Luyi Gui, The Paul Merage School of Business, UC Irvine, Irvine, CA, 92697-3125, United States 1 - Operational Challenges in a Medical Transportation Platform in India Gonzalo Romero, Rotman, University of Toronto, 91 Ferrier Avenue, Toronto, ON, M4K 3H6, Canada, Andre Du Pin Calmon A centralized ambulance dispatch center, like 911 in the U.S., does not exist in many developing countries. Therefore, people that need medical transportation must call their local hospital or hire private ambulances. This translates into long waiting times for patients and costly routes for the ambulances. A medical transportation platform can address this problem by aggregating and dispatching life-saving services. Motivated by our ongoing collaboration with a company in India, we model and analyze the operational challenges of managing a healthcare transportation company in an emerging market. 2 - Impacts of Logistics Information on Sales: The Evidence from Taobao Leading e-commerce companies are rapidly expanding their logistics networks to deliver items faster and more reliably. This improved logistics quality drives customers to share their positive experiences online. Using a dataset from China’s largest e-marketplace platform, we empirically explore the role of logistics services and their effect on online consumer purchasing behaviors. 3 - Supplier Encroachment Deterrence Through Forecasting Scheme Design Guangrui Ma, Tianjin University, 92 Weijin Road, 25A, CoME, Tianjin, 300072, China, Ying-Ju Chen We study how a retailer should design its forecasting scheme facing the supplier encroachment risk, under truthful information sharing agreement with its supplier. We identify three different forecasting schemes that should be implemented according to competition intensity between the indirect channel Shu Hu, National Dong Hwa University, 462 Wenyuan Road, Ningbo, 610031, China, Luyi Gui, Jiaru Bai, Zujun Ma, Rick So This paper develops an analytical framework for designing effective subsidy scheme to motivate consumer trade-ins. We find that a sharing subsidy scheme is always more effective than a fixed subsidy. We further derive analytical results which illustrate how the government should allocate its total available budget for multiple products based on the individual product and market characteristics. Based on the results from our analysis and numerical experiments, we devise a simple budget allocation mechanism that provides near-optimal solutions. Ying Rong, Shanghai Jiao Tong University, No. 1 Lane 9, Yunwushan Road, Shanghai, 200051, China, Jifeng Luo, Huan Zheng and direct channel, and supplier’s channel investment efficiency. 4 - Optimal Subsidy Schemes and Budget Allocations for Government Trade-in Programs

n TA17 North Bldg 127C Informational and Reputational Issues in Value Chains Sponsored: Manufacturing & Service Oper Mgmt/Supply Chain Sponsored Session Chair: Haresh B. Gurnani, Wake Forest University, Winston Salem, NC, 27106, United States Chair: Saibal Ray, McGill University, Montreal, QC, Canada 1 - Managing Reputation Risk in Supply Chains: The Role of Contract-embedded Insurance Vibhuti Dhingra, University of British Columbia, 2053 Main Mall, Vancouver, BC, V6T1Z2, Canada, Harish Krishnan We study the role of contract-embedded insurance in managing a buyer’s reputation risk arising due to supplier responsibility violations. We find that insurance can both decrease and increase supplier violations. When insurance reduces violations, the buyer benefits from a lower reputation risk. But if reputation costs are low, the buyer can use insurance to squeeze the supplier’s margin even if this increases violations. We then consider the impact of supplier noncompliance on the buying firm’s investors. We show that a salary-based compensation for the buying firm’s manager is insufficient to align incentives across the three tiers, but risk-based bonus compensation schemes can be effective. 2 - The Informational Role of Buyback Contracts Haresh B. Gurnani, Wake Forest University, 319 Farrell Hall, School of Business, 1834 Wake Forest Road, Winston Salem, NC, 27106, United States, Shouqiang Wang, Upender Subramanian Retailers often carry inventory in anticipation of demand. Manufacturers can encourage them to stock sufficient inventory by offering to buyback any unsold inventory at a pre-specified price using a buyback contract. We examine the manufacturer’s use of a buyback contract as a signaling mechanism when the retailer is less informed about either the manufacturer’s reliability of honoring its buyback commitment or about it product’s demand potential. 3 - The Perils of Omniscient Online Retailers Saibal Ray, McGill University, Desautels Faculty of Management, 1001 Sherbrooke Street W, Montreal, QC, H3A 1G5, Canada, Michelle Y. Lu, Yuxin Chen With the help of big data technologies, online retailers now become omniscient, i.e., knowing everything about consumer preferences, and product matches between firms and consumers. Online retailers can strategically sell firms information about consumer preferences or withhold matching information but charge firms to reveal them to consumers. Is it good to have such powerful retailers? Our research analyzes this complicated issue and investigates the welfare implications on consumers. n TA18 North Bldg 128A Joint Session BMI/Practice Curated: Empirical Research on Marketplace Innovation Emerging Topic: Business Model Innovation Emerging Topic Session Chair: Ashish Kabra, INSEAD, Fontainebleau, 77305, France 1 - Do P2P Ride-Hailing Platforms Lead to Pooling or Crowding? Quasi-Experimental Evidence from Uber’s Entry in California Suvrat Dhanorkar, Pennsylvania State University, 466 Business Building, University Park, PA, 16802, United States Taking advantage of Uber’s staggered entry into various geographic markets in California, we execute a regression-based difference-in-difference design to estimate the pooling benefits of ride-sharing services. 2 - Designing Incentives to Scale Marketplaces Ashish Kabra, INSEAD, Boulevard de constance, Fontainebleau, 77305, France Marketplace operators run aggressive incentive schemes to achieve scale, that is key to the efficacy, survival and eventual domination of a marketplace. This study quantifies and compares the effect of incentives given to the “buyer side and “seller side using data from a leading ride-hailing market. We build a structural model to accurately capture the driver and passenger response to incentives, and the nature of incentives. Driver effort on the platform is unobserved, for which we devise a novel local matching model based imputation method. We find that in short-term (current week) passenger incentives are more effective while the opposite is true in the long-term (next 3 months).

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