Newsvendor problem under complete uncertainty: a case of innovative products

Helena Gaspars-Wieloch

Abstract

The paper presents a new scenario-based decision rule for the classical version of the newsvendor problem (NP) under complete uncertainty (i.e. uncertainty with unknown probabilities). So far, NP has been analyzed under uncertainty with known probabilities or under uncertainty with partial information (probabilities known incompletely). The novel approach is designed for the sale of new, innovative products, where it is quite complicated to define probabilities or even probability-like quantities, because there are no data available for forecasting the upcoming demand via statistical analysis. The new procedure described in the contribution is based on a hybrid of Hurwicz and Bayes decision rules. It takes into account the decision maker’s attitude towards risk (measured by coefficients of optimism and pessimism) and the dispersion (asymmetry, range, frequency of extremes values) of payoffs connected with particular order quantities. It does not require any information about the probability distribution.
Author Helena Gaspars-Wieloch (WIiGE / KBO)
Helena Gaspars-Wieloch,,
- Department of Operations Research
Journal seriesCentral European Journal of Operations Research, ISSN 1435-246X, (A 20 pkt)
Issue year2017
Vol25
No3
Pages561-585
Publication size in sheets1.2
Keywords in EnglishNewsvendor problem, Complete uncertainty, Scenario-based decision rule, Risk aversion, One-shot decision, Innovative products
ASJC Classification1803 Management Science and Operations Research
DOIDOI:10.1007/s10100-016-0458-3
URL http://link.springer.com/article/10.1007/s10100-016-0458-3
Languageen angielski
Score (nominal)20
Score sourcejournalList
ScoreMinisterial score = 20.0, 12-03-2020, ArticleFromJournal
Publication indicators WoS Citations = 5; Scopus SNIP (Source Normalised Impact per Paper): 2017 = 0.854; WoS Impact Factor: 2017 = 0.73 (2) - 2017=0.948 (5)
Citation count*20 (2020-07-12)
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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