Sourcing for Online Marketplaces with Demand and Price Uncertainty

Gaur, V., Osadchiy, N., Seshadri, S., & Subrahmanyam, M. G. (2023). Sourcing for online marketplaces with demand and price uncertainty. Production and Operations Management, 00, 1– 19. https://doi.org/10.1111/poms.14023

43 Pages Posted: 22 Oct 2015 Last revised: 7 Jul 2023

See all articles by Vishal Gaur

Vishal Gaur

Cornell University - Samuel Curtis Johnson Graduate School of Management

Nikolay Osadchiy

Emory University - Goizueta Business School

Sridhar Seshadri

University of Illinois at Urbana Champaign; Indian School of Business

Marti G. Subrahmanyam

New York University (NYU) - Leonard N. Stern School of Business

Date Written: October 1, 2020

Abstract

Our paper is motivated by a manufacturer that sells a single seasonal product through multiple retailers competing on an online marketplace, such as Amazon marketplace. Selling price uncertainty and evolution of forecasts of price and demand are key features of the online marketplace. Sourcing choices are differentiated by cost and available lead times -- delaying to a shorter lead time is more expensive, but yield more accurate information about future selling price and demand. Thus, ahead of the season, each retailer faces a continuous-time decision problem about when to place an order with the manufacturer and in what quantity. The manufacturer is interested in knowing the ordering pattern of the retailers in order to plan its production schedule. We consider two sourcing strategies varying in the flexibility of order timing: an optimal pre-committed ordering time strategy and an optimal time-flexible ordering strategy. Under the latter strategy, the optimal order time follows a double threshold policy in the selling price variable: it is optimal to order if the price is within a certain band, and wait otherwise. By characterizing both strategies, we identify scenarios when time-flexible ordering can be beneficial for the retailer, the manufacturer, and the supply chain as a whole. The predictions of our model are consistent with the experience of a large U.S. manufacturer that motivated our study.

Keywords: Supply chain management, Stochastic inventory theory, Optimal stopping.

Suggested Citation

Gaur, Vishal and Osadchiy, Nikolay and Seshadri, Sridhar and Subrahmanyam, Marti G., Sourcing for Online Marketplaces with Demand and Price Uncertainty (October 1, 2020). Gaur, V., Osadchiy, N., Seshadri, S., & Subrahmanyam, M. G. (2023). Sourcing for online marketplaces with demand and price uncertainty. Production and Operations Management, 00, 1– 19. https://doi.org/10.1111/poms.14023 , Available at SSRN: https://ssrn.com/abstract=2677045 or http://dx.doi.org/10.2139/ssrn.2677045

Vishal Gaur

Cornell University - Samuel Curtis Johnson Graduate School of Management ( email )

Ithaca, NY 14853
United States

HOME PAGE: http://www.johnson.cornell.edu/faculty/profiles/Gaur/

Nikolay Osadchiy (Contact Author)

Emory University - Goizueta Business School ( email )

1300 Clifton Road
Atlanta, GA 30322
United States

HOME PAGE: http://www.nikolayosadchiy.com

Sridhar Seshadri

University of Illinois at Urbana Champaign ( email )

1206 South Sixth Street
Champaign, IL 61820
United States

Indian School of Business ( email )

Hyderabad, Gachibowli 500 019
India

Marti G. Subrahmanyam

New York University (NYU) - Leonard N. Stern School of Business ( email )

44 West 4th Street
Suite 9-160
New York, NY NY 10012
United States

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