TY - JOUR
KW - Supply chain management
KW - Supply chain risks
KW - Carbon emissions
KW - Discrete-event simulation
KW - Analytic hierarchy process
KW - Fast moving consumer goods
AU - Marcus Brandenburg
AB - Formal models that support multi-criteria decision making represent a strongly growing area in sustainable supply chain management research. However, uncertainties and risks are seldom considered in quantitative models for green supply chain (SC) design. The paper at hand suggests a hybrid approach to configure an eco-efficient SC for a new product under consideration of economic and environmental risks. Discrete-event simulation is applied to assess the financial, operational and environmental performance of different SC configuration options while the value-at-risk concept is adapted to evaluate related SC risks. The analytic hierarchy process is employed to solve the resulting multi-criteria decision problem of choosing the best option. The approach is illustrated at a case example of a fast moving consumer goods manufacturer.
BT - Omega
DO - 10.1016/j.omega.2016.09.002
N2 - Formal models that support multi-criteria decision making represent a strongly growing area in sustainable supply chain management research. However, uncertainties and risks are seldom considered in quantitative models for green supply chain (SC) design. The paper at hand suggests a hybrid approach to configure an eco-efficient SC for a new product under consideration of economic and environmental risks. Discrete-event simulation is applied to assess the financial, operational and environmental performance of different SC configuration options while the value-at-risk concept is adapted to evaluate related SC risks. The analytic hierarchy process is employed to solve the resulting multi-criteria decision problem of choosing the best option. The approach is illustrated at a case example of a fast moving consumer goods manufacturer.
PY - 2017
SP - 58
EP - 76
T2 - Omega
TI - A hybrid approach to configure eco-efficient supply chains under consideration of performance and risk aspects
UR - https://www.sciencedirect.com/science/article/pii/S0305048316305990
VL - 70
SN - 0305-0483
ER -