Conference proceeding
Asymmetric Information Effect on Transshipment Reporting Strategy
PROCEEDINGS OF THE TENTH INTERNATIONAL CONFERENCE ON MANAGEMENT SCIENCE AND ENGINEERING MANAGEMENT, v 502, pp 445-454
01 Jan 2017
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Lateral transshipments in multi-echelon stochastic inventory system imply that locations at the same echelon of a supply chain share inventories in some way, in order to deal with local uncertainties in demands. While a large body of research studies inventory transshipment issues, few papers have considered the effect of information on transshipment reporting decisions. We analyze the transshipment decisions after demand realization under a decentralized setting with asymmetric information concerning demand. In this research, the shortage demand information at one retailer is not public and the shortage retailer may manipulate this number in order to obtain the optimal transshipment amount. We not only demonstrate that the shortage retailer can distort the actual shortage number to improve its profit, but also identify when to use under-reporting or over-reporting policy. Furthermore, we also explore the reporting policy when the surplus retailer only informs the shortage retailer its surplus inventory distribution or mean and variance.
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Details
- Title
- Asymmetric Information Effect on Transshipment Reporting Strategy
- Creators
- Yi Liao - Southwestern Univ Finance & Econ, Sch Business Adm, Chengdu 611130, Sichuan, Peoples R ChinaWenjing Shen - Drexel UniversityBen Lev - Drexel University
- Contributors
- J Xu (Editor)A Hajiyev (Editor)S Nickel (Editor)M Gen (Editor)
- Publication Details
- PROCEEDINGS OF THE TENTH INTERNATIONAL CONFERENCE ON MANAGEMENT SCIENCE AND ENGINEERING MANAGEMENT, v 502, pp 445-454
- Series
- Advances in Intelligent Systems and Computing
- Publisher
- Springer Nature
- Number of pages
- 10
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Web of Science ID
- WOS:000407613300040
- Scopus ID
- 2-s2.0-84984863625
- Other Identifier
- 991019167642404721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Interdisciplinary Applications