File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Data and Risk Analytics for Production Planning

TitleData and Risk Analytics for Production Planning
Authors
KeywordsG32 Financial Risk and Risk Management
M11 Production management
Risk management
Hedging
Operational risk
Issue Date2019
PublisherNow 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?
AbstractWe 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 Identifierhttp://hdl.handle.net/10722/272720
ISSN
2023 SCImago Journal Rankings: 0.251

 

DC FieldValueLanguage
dc.contributor.authorWang, L-
dc.contributor.authorYao, DD-
dc.date.accessioned2019-08-06T09:15:18Z-
dc.date.available2019-08-06T09:15:18Z-
dc.date.issued2019-
dc.identifier.citationFoundations and Trends in Technology, Information and Operations Management, 2019, v. 12 n. 2-3, p. 201-218-
dc.identifier.issn1571-9545-
dc.identifier.urihttp://hdl.handle.net/10722/272720-
dc.description.abstractWe 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.languageeng-
dc.publisherNow Publishers Inc. The Journal's web site is located at https://www.nowpublishers.com/TOM-
dc.relation.ispartofFoundations and Trends in Technology, Information and Operations Management-
dc.rightsThe final publication is available from now publishers via http://dx.doi.org/10.1561/0200000086-
dc.subjectG32 Financial Risk and Risk Management-
dc.subjectM11 Production management-
dc.subjectRisk management-
dc.subjectHedging-
dc.subjectOperational risk-
dc.titleData and Risk Analytics for Production Planning-
dc.typeArticle-
dc.identifier.emailWang, L: lwang98@hku.hk-
dc.identifier.authorityWang, L=rp02321-
dc.description.naturepostprint-
dc.identifier.doi10.1561/0200000086-
dc.identifier.scopuseid_2-s2.0-85062912830-
dc.identifier.hkuros300604-
dc.identifier.volume12-
dc.identifier.issue2-3-
dc.identifier.spage201-
dc.identifier.epage218-
dc.publisher.placeUnited States-
dc.identifier.issnl1571-9545-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats