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Journal of Applied Sciences

Year: 2013 | Volume: 13 | Issue: 23 | Page No.: 5611-5615
DOI: 10.3923/jas.2013.5611.5615
Two-ordering Newsvendor Based on CVaR Decision Criteria with Information Updating
Yong Han, Bei Zhao and Hua-Ming Song

Abstract: In this study, we investigate the two-ordering newsvendor with demand information updating. In this background, the retailers can take advantage of the demand information that gathered between the first stage and the second stage to update demand forecast with Bayesian principle. We then establish the two-stage ordering model for maximizing the conditional value at risk (denoted as CVaR) of optimal profits and use dynamic programming methods to analyze the existence and uniqueness of the optimal solution. Next, we design the optimal solution algorithm and give numerical analysis with a real case example in which we discuss that the retailer's decision-making is related to the risk coefficient. The higher the degree of the risk (the smaller of) is, the smaller the value of profits is. The research results show that risk-neutral model is only a special case of CVaR decision rule. This study extends the two-ordering newsvendor from risk-neutral case to CVaR case with information updating.

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How to cite this article
Yong Han, Bei Zhao and Hua-Ming Song, 2013. Two-ordering Newsvendor Based on CVaR Decision Criteria with Information Updating. Journal of Applied Sciences, 13: 5611-5615.

Keywords: Newsvendor, two ordering, conditional value-at-risk (CVaR) and information updating

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