Publication Type
Journal Article
Version
publishedVersion
Publication Date
2008
Abstract
This paper discusses the importance of and a solution to separating the information flow from the physical product flow in a supply chain. Motivated by the inefficient demand forecast caused by information asymmetry and lack of an incentive among supply chain partners to share valuable information, we propose a radically new framework called collective outsourcing to market (COM) to address many information supply chain design challenges. To validate the COM framework, we consider a supply chain with one manufacturer and multiple downstream retailers. Retailers privately acquire demand forecast information that they do not have incentive to share horizontally with other retailers or vertically with the upstream manufacturer. We consider two alternative market mechanisms that can be used to outsource the information-intensive demand forecasting task for the whole supply chain. The specially organized market can be viewed as a cost effective way of acquiring quality information that, at the same time, aligns individual retailers' incentives to credibly share their private information. We further discuss the real world implementation issues including market design and the costs and benefits of proposed solutions.
Keywords
information supply chain, market mechanism, outsourcing, demand forecasting
Discipline
Computer Sciences | Management Information Systems | Numerical Analysis and Scientific Computing
Research Areas
Information Systems and Management
Publication
Journal of the Association for Information Systems
Volume
9
Issue
4
First Page
98
Last Page
118
ISSN
1536-9323
Identifier
10.17705/1jais.00157
Publisher
Association for Information Systems
Citation
FANG, Fang; GUO, Zhiling; and WHINSTON, Andrew B..
Collective Outsourcing to Market (COM): A Market-Based Framework for Information Supply Chain Outsourcing. (2008). Journal of the Association for Information Systems. 9, (4), 98-118.
Available at: https://ink.library.smu.edu.sg/sis_research/1862
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.17705/1jais.00157
Included in
Management Information Systems Commons, Numerical Analysis and Scientific Computing Commons