TY - JOUR
T1 - Risk control for staff planning in e-commerce warehouses
AU - Wruck, S.
AU - Vis, I.F.A.
AU - Boter, J.
PY - 2017
Y1 - 2017
N2 - Internet sale supply chains often need to fulfil quickly small orders for many customers. The resulting high demand and planning uncertainties pose new challenges for e-commerce warehouse operations. Here, we develop a decision support tool to assist managers in selecting appropriate risk policies and making staff planning decisions in uncertain conditions. Multistage stochastic modelling has been used to analyse risk optimisation approaches and expected value-based optimisation. Exhaustive numerical and practical validations have been performed to test the tool’s applicability. We demonstrate, using a Dutch e-commerce warehouse, that the multi-period conditional value at risk appears to be most applicable.
AB - Internet sale supply chains often need to fulfil quickly small orders for many customers. The resulting high demand and planning uncertainties pose new challenges for e-commerce warehouse operations. Here, we develop a decision support tool to assist managers in selecting appropriate risk policies and making staff planning decisions in uncertain conditions. Multistage stochastic modelling has been used to analyse risk optimisation approaches and expected value-based optimisation. Exhaustive numerical and practical validations have been performed to test the tool’s applicability. We demonstrate, using a Dutch e-commerce warehouse, that the multi-period conditional value at risk appears to be most applicable.
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U2 - 10.1080/00207543.2016.1207816
DO - 10.1080/00207543.2016.1207816
M3 - Article
SN - 0020-7543
VL - 55
SP - 6453
EP - 6469
JO - International Journal of Production Research
JF - International Journal of Production Research
IS - 21
ER -