Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/118403
Title: Sourcing decision under interconnected risks: an application of mean–variance preferences approach
Authors: Mukherjee, S.
Padhi, S. S.
Issue Date: 2022
Citation: Mukherjee S. Sourcing decision under interconnected risks: an application of mean–variance preferences approach / S. Mukherjee, S. S. Padhi // Annals of Operations Research. — 2022. — Vol. 313. — Iss. 2. — P. 1243-1268.
Abstract: Supply chains are customarily associated with multiple interconnected risks originated from supply side, demand side, or from the unanticipated background uncertainties faced by a firm. Also, effective functioning of supply chain hinges on sourcing decisions of inputs (raw materials). Therefore, there is a striking need to analyse the risk preference of the decision maker while going for optimal sourcing decision under varying degree of interconnected supply chain risks. This study addresses this issue by analysing the comparative static effects under interconnected supply chain risks for a risk averse decision-maker, manufacturing and selling products in a regulated market under perfect competition. The decision-maker faces not only supply-side risk (due to random input material prices) but also interconnected risks arising out of background risk (setup costs risk) and demand-side risk (output prices risk). With preferences defined over the mean and standard deviation of the uncertain final profit, this study illustrates the effects of the changes in the pairwise correlations between the three above mentioned risks on the optimum input choice of the manufacturer. To contextualise this study, an India-based generic drug manufacturer cum seller has been considered as a case in the parametric example of our model. Adaptation of the mean–variance framework helps obtaining all the results in terms of the relative trade-off between risk and return, with simple yet intuitive interpretations. © 2022, The Author(s).
Keywords: DECISION ANALYSIS
INTERCONNECTED RISKS
MEAN–VARIANCE MODEL
SOURCING DECISION
SUPPLY CHAIN RISK
URI: http://elar.urfu.ru/handle/10995/118403
Access: info:eu-repo/semantics/openAccess
SCOPUS ID: 85122412317
WOS ID: 000739812100002
PURE ID: 30457895
DOI: 10.1007/s10479-021-04485-3
Sponsorship: University of Nottingham
The authors are grateful to the guest editors (Prof. (Dr) Jean-Luc Prigent, Prof. (Dr) Ephraim Clark, and Prof. (Dr) Giovanni Barone Adesi) and two anonymous referees for their constructive comments on its submitted version of December 2019. The authors are also grateful to Prof. (Dr) Stephen M. Wagner (ETH Zurich) and Prof. (Dr) Udo Broll (TU Dresden) for their inputs on another past version of this research, which had been drafted as a CREDIT WP version [Mukherjee, S. & Padhi, S.S. (2018). Risk Connectivity and Risk Mitigation: An Analytical Framework , CREDIT WP Series No. 18/11, University of Nottingham (UK). Available at: <https://www.nottingham.ac.uk/credit/documents/papers/2018/18-11.pdf >]. Both the submitted version of December 2019 and this present revision are substantially different from the above-mentioned draft. The usual disclaimers are applicable.
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