Technical Note---A Risk-Averse Newsvendor Model Under the CVaR Criterion

Youhua (Frank) Chen (), Minghui Xu () and Zhe George Zhang ()
Additional contact information
Youhua (Frank) Chen: Department of Systems Engineering and Engineering Management, Chinese University of Hong Kong, Shatin, N.T., Hong Kong
Minghui Xu: School of Economics and Management, Wuhan University, Wuhan 430072, China
Zhe George Zhang: Department of Decision Science, Western Washington University, Bellingham, Washington 98225, and Faculty of Business Administration, Simon Fraser University, Burnaby, British Columbia, Canada V5A 1S6

Operations Research, 2009, vol. 57, issue 4, 1040-1044

Abstract: The classical risk-neutral newsvendor problem is to decide the order quantity that maximizes the one-period expected profit. In this note, we consider a risk-averse newsvendor with stochastic price-dependent demand. We adopt Conditional Value-at-Risk ( CVaR ), a risk measure commonly used in finance, as the decision criterion. The aim of our study is to investigate the optimal pricing and ordering decisions in such a setting. For both additive and multiplicative demand models, we provide sufficient conditions for the uniqueness and existence of the optimal policy. Comparative statics show the monotonicity properties and other characteristics of the optimal pricing and ordering decisions. We also compare our results with those of the newsvendor with a risk-neutral attitude and a general utility function.

Keywords: inventory; risk; perishable/aging items; marketing; pricing (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (53)

Downloads: (external link)
http://dx.doi.org/10.1287/opre.1080.0603 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:57:y:2009:i:4:p:1040-1044

Access Statistics for this article

More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().