File Download
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1561/0200000086
- Scopus: eid_2-s2.0-85062912830
- Find via
Supplementary
-
Citations:
- Scopus: 0
- Appears in Collections:
Article: Data and Risk Analytics for Production Planning
Title | Data and Risk Analytics for Production Planning |
---|---|
Authors | |
Keywords | G32 Financial Risk and Risk Management M11 Production management Risk management Hedging Operational risk |
Issue Date | 2019 |
Publisher | Now Publishers Inc. The Journal's web site is located at https://www.nowpublishers.com/TOM |
Citation | Foundations and Trends in Technology, Information and Operations Management, 2019, v. 12 n. 2-3, p. 201-218 How to Cite? |
Abstract | We examine the classical productional planning model, where a capacity decision that has to be made at the beginning of the planning horizon is the primary means to protect against demand uncertainty. We provide a critique on the model focusing on its profit maximizing objective, its underlying assumptions on demand and related forecasting scheme, and its overall business relevance (or the lack thereof); and we do so in the context of data, risk and analytics. Specifically, we will consider minimizing a shortfall risk relative to a profit target, with a demand model that captures impacts from the financial market and can be learned from data sets that are application specific. With a jointly optimized production and hedging strategy, we show the new model outperforms traditional approaches in risk mitigation as well as in expected profit. © 2019 Now Publishers Inc. All rights reserved. |
Persistent Identifier | http://hdl.handle.net/10722/272720 |
ISSN | 2023 SCImago Journal Rankings: 0.251 |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Wang, L | - |
dc.contributor.author | Yao, DD | - |
dc.date.accessioned | 2019-08-06T09:15:18Z | - |
dc.date.available | 2019-08-06T09:15:18Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Foundations and Trends in Technology, Information and Operations Management, 2019, v. 12 n. 2-3, p. 201-218 | - |
dc.identifier.issn | 1571-9545 | - |
dc.identifier.uri | http://hdl.handle.net/10722/272720 | - |
dc.description.abstract | We examine the classical productional planning model, where a capacity decision that has to be made at the beginning of the planning horizon is the primary means to protect against demand uncertainty. We provide a critique on the model focusing on its profit maximizing objective, its underlying assumptions on demand and related forecasting scheme, and its overall business relevance (or the lack thereof); and we do so in the context of data, risk and analytics. Specifically, we will consider minimizing a shortfall risk relative to a profit target, with a demand model that captures impacts from the financial market and can be learned from data sets that are application specific. With a jointly optimized production and hedging strategy, we show the new model outperforms traditional approaches in risk mitigation as well as in expected profit. © 2019 Now Publishers Inc. All rights reserved. | - |
dc.language | eng | - |
dc.publisher | Now Publishers Inc. The Journal's web site is located at https://www.nowpublishers.com/TOM | - |
dc.relation.ispartof | Foundations and Trends in Technology, Information and Operations Management | - |
dc.rights | The final publication is available from now publishers via http://dx.doi.org/10.1561/0200000086 | - |
dc.subject | G32 Financial Risk and Risk Management | - |
dc.subject | M11 Production management | - |
dc.subject | Risk management | - |
dc.subject | Hedging | - |
dc.subject | Operational risk | - |
dc.title | Data and Risk Analytics for Production Planning | - |
dc.type | Article | - |
dc.identifier.email | Wang, L: lwang98@hku.hk | - |
dc.identifier.authority | Wang, L=rp02321 | - |
dc.description.nature | postprint | - |
dc.identifier.doi | 10.1561/0200000086 | - |
dc.identifier.scopus | eid_2-s2.0-85062912830 | - |
dc.identifier.hkuros | 300604 | - |
dc.identifier.volume | 12 | - |
dc.identifier.issue | 2-3 | - |
dc.identifier.spage | 201 | - |
dc.identifier.epage | 218 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 1571-9545 | - |