Partner with a Third-Party Delivery Service or Not? A Prediction- and-Decision Tool for Restaurants Facing Takeout Demand Surges during a Pandemic

Journal article

Peer reviewed

Huiwen Jia, Siqian Shen, Jorge Alberto Ramírez García, Cong Shi and Univ. of Michigan, Ann Arbor, MI (United States)

Service science (Hanover, Md.), Vol.14(2), pp.139-155

2022-06-01

Abstract

autoregressive-moving-average (ARMA)

demand uncertainty

on-demand grocery or food delivery

stochastic integer programming

susceptible-infected-recovered (SIR) model

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Title: Partner with a Third-Party Delivery Service or Not? A Prediction- and-Decision Tool for Restaurants Facing Takeout Demand Surges during a Pandemic
Creators: Huiwen Jia - University of Michigan
Siqian Shen - University of Michigan
Jorge Alberto Ramírez García - University of Monterrey
Cong Shi - University of Michigan
Univ. of Michigan, Ann Arbor, MI (United States)
Publication Details: Service science (Hanover, Md.), Vol.14(2), pp.139-155
Number of pages: 17
Grant note: CMMI-2041745 / National Science Foundation (http://data.elsevier.com/vocabulary/SciValFunders/100000001) CMMI-2041745 / National Science Foundation (100000001) DE-SC0018018 / U.S. Department of Energy (http://data.elsevier.com/vocabulary/SciValFunders/100000015) DE-SC0018018 / U.S. Department of Energy (100000015)
Academic Unit: Miami Herbert Business School; MHBS - Management
Language: English
Resource Type: Journal article
Record Identifier: 991032796283902976