Article: A portfolio approach to managing procurement risk using multi-stage stochastic programming
| Title | A portfolio approach to managing procurement risk using multi-stage stochastic programming |
|---|---|
| Authors | Shi, Y1 2 Wu, F3 Chu, LK1 Sculli, D1 Xu, YH1 |
| Keywords | portfolio procurement approach procurement risk risk mitigation stochastic programming |
| Issue Date | 2011 |
| Publisher | Palgrave Macmillan Ltd. The Journal's web site is located at http://www.palgrave-journals.com/jors/index.html |
| Citation | Journal Of The Operational Research Society, 2011, v. 62 n. 11, p. 1958-1970 [How to Cite?] DOI: http://dx.doi.org/10.1057/jors.2010.149 |
| Abstract | Procurement is a critical supply chain management function that is susceptible to risk, due mainly to uncertain customer demand and purchase price volatility. A procurement approach in the form of a portfolio that incorporates the common procurement means is proposed. Such means include long-term contracts, spot procurements and option-based supply contracts. The objective is to explore possible synergies among the various procurement means, and so be able to produce optimal or near optimal results in profit while mitigating risk. The implementation of the portfolio approach is based on a multi-stage stochastic programming model in which replenishment decisions are made at various stages along a time horizon, with replenishment quantities being determined by simultaneously considering the stochastic demand and the price volatility of the spot market. The model attempts to minimise the risk exposure of procurement decisions measured as conditional value-at-risk. Numerical experiments to test the effectiveness of the proposed model are performed using demand data from a large air conditioner manufacturer in China and price volatility data from the Shanghai steel market. The results indicate that the proposed model can fairly reliably outperform other approaches, especially when either the demand and/or prices exhibit significant variability. © 2011 Operational Research Society Ltd. All rights reserved. |
| ISSN | 0160-5682 2011 Impact Factor: 0.971 2011 SCImago Journal Rankings: 0.045 |
| DOI | http://dx.doi.org/10.1057/jors.2010.149 |
| ISI Accession Number ID | WOS:000295899100006 |
| References | References in Scopus |
| dc.contributor.author | Shi, Y |
|---|---|
| dc.contributor.author | Wu, F |
| dc.contributor.author | Chu, LK |
| dc.contributor.author | Sculli, D |
| dc.contributor.author | Xu, YH |
| dc.date.accessioned | 2012-02-03T06:12:55Z |
| dc.date.available | 2012-02-03T06:12:55Z |
| dc.date.issued | 2011 |
| dc.description.abstract | Procurement is a critical supply chain management function that is susceptible to risk, due mainly to uncertain customer demand and purchase price volatility. A procurement approach in the form of a portfolio that incorporates the common procurement means is proposed. Such means include long-term contracts, spot procurements and option-based supply contracts. The objective is to explore possible synergies among the various procurement means, and so be able to produce optimal or near optimal results in profit while mitigating risk. The implementation of the portfolio approach is based on a multi-stage stochastic programming model in which replenishment decisions are made at various stages along a time horizon, with replenishment quantities being determined by simultaneously considering the stochastic demand and the price volatility of the spot market. The model attempts to minimise the risk exposure of procurement decisions measured as conditional value-at-risk. Numerical experiments to test the effectiveness of the proposed model are performed using demand data from a large air conditioner manufacturer in China and price volatility data from the Shanghai steel market. The results indicate that the proposed model can fairly reliably outperform other approaches, especially when either the demand and/or prices exhibit significant variability. © 2011 Operational Research Society Ltd. All rights reserved. |
| dc.description.nature | Link_to_subscribed_fulltext |
| dc.identifier.citation | Journal Of The Operational Research Society, 2011, v. 62 n. 11, p. 1958-1970 [How to Cite?] DOI: http://dx.doi.org/10.1057/jors.2010.149 |
| dc.identifier.doi | http://dx.doi.org/10.1057/jors.2010.149 |
| dc.identifier.epage | 1970 |
| dc.identifier.hkuros | 198402 |
| dc.identifier.isi | WOS:000295899100006 |
| dc.identifier.issn | 0160-5682 2011 Impact Factor: 0.971 2011 SCImago Journal Rankings: 0.045 |
| dc.identifier.issue | 11 |
| dc.identifier.scopus | eid_2-s2.0-80053497109 |
| dc.identifier.spage | 1958 |
| dc.identifier.uri | http://hdl.handle.net/10722/144533 |
| dc.identifier.volume | 62 |
| dc.language | eng |
| dc.publisher | Palgrave Macmillan Ltd. The Journal's web site is located at http://www.palgrave-journals.com/jors/index.html |
| dc.publisher.place | United Kingdom |
| dc.relation.ispartof | Journal of the Operational Research Society |
| dc.relation.references | References in Scopus |
| dc.rights | Journal of the Operational Research Society. Copyright © Palgrave Macmillan Ltd. |
| dc.subject | portfolio procurement approach |
| dc.subject | procurement risk |
| dc.subject | risk mitigation |
| dc.subject | stochastic programming |
| dc.title | A portfolio approach to managing procurement risk using multi-stage stochastic programming |
| dc.type | Article |
Author Affiliations
- The University of Hong Kong
- South China University of Technology
- Xi'an Jiaotong University

