The risk-averse newsvendor problem under spectral risk measures: A classification with extensions
Emel Arıkan and
Johannes Fichtinger
European Journal of Operational Research, 2017, vol. 256, issue 1, 116-125
Abstract:
We study the risk-averse newsvendor problem by defining the objective function as a spectral risk measure. We analyze the problem under different types of return formulations, focusing on the impact of risk aversion and cost parameters on the optimal ordering decision. We show that the monotonicity of the return function with respect to random demand determines the structural properties of the problem. When the return function is monotone in demand realization, optimal order quantity does not depend on the return margin but only on the overage and underage costs, and it has a monotone relation to risk aversion. However, if return is non-monotone in demand impact of risk aversion depends on the specific setting and it can also be non-monotone. Additionally, it is non-increasing in the margin which leads to varying impact of selling price under distinct settings.
Keywords: Inventory; Newsvendor; Risk-aversion; Spectral risk measures; Shortage cost (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0377221716304222
Full text for ScienceDirect subscribers only
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:eee:ejores:v:256:y:2017:i:1:p:116-125
DOI: 10.1016/j.ejor.2016.06.002
Access Statistics for this article
European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati
More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().