Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

 
 
Session Overview
Session
TC8 - RM6: Choice and promotions
Time:
Tuesday, 28/June/2022:
TC 14:00-15:30

Session Chair: Yi Chen
Location: Forum 12


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Presentations

Fulfillment by platform: Antitrust and upstream market power

Amandeep Singh1, Jiding Zhang2, Senthil Veeraraghavan1

1The Wharton School, U of Pennsylvania, USA; 2New York University, NY

We examine whether mere adoption of fulfillment services offered by

platforms distorts competition by using data from a leading online retailing marketplace to empirically evaluate the effect on upstream

supply echelons. We find that evidence for regulatory views as the surplus welfare is absorbed by the platform. Smaller merchants with lower margin, are forced to increase price to remain profitable with platform fulfillment, leading to a price disadvantage compared to the bigger suppliers.



Contracting Strategies for Price competing Firms under Demand Uncertainty

You Wu, Anne Lange, Benny Mantin

University of Luxembourg, Luxembourg

Capacity-constrained asset providers (APs) often compete over prices when they trade their transport capacities with logistics service providers (LSPs) via spot markets. To circumvent demand uncertainty, an AP and an LSP can negotiate a contract to secure sales and capacity, respectively. We propose a two-stage game theoretical model to study the trade-off of balancing the contract and spot market by characterizing the contracting and pricing strategies under competition and demand uncertainty.



How to display promotions when customers search?

Yi Chen1, Jing Dong2, Fanyin Zheng2

1Hong Kong University of Science and Technology, Hong Kong S.A.R. (China); 2Columbia University

We study the impact of promotion display for online retail platforms where customers search. Utilizing a dataset set which contains detailed behavior information, we estimate a search and purchase model. Accurate estimation also enables us to evaluate different promotion display schemes and design policies that can improve the revenue. Through counterfactual analysis, we demonstrate that our policies can improve the revenue for some product categories by 2-4%.



 
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