TY - JOUR
T1 - Strategic Global Supply Chain Network Design
T2 - How Decision Analysis Combining MILP and AHP on a Pareto Front Can Improve Decision-making
AU - Reich, Juri
AU - Kinra, Aseem
AU - Kotzab, Herbert
AU - Brusset, Xavier
N1 - Published online: 25 Nov 2020.
PY - 2021/3
Y1 - 2021/3
N2 - Integrating a broad range of information types and finding trade-offs between conflicting goals is a challenge in global supply chain network design (GSCND). Effective decision support systems (DSS) should be user-friendly, provide transparency, and support human judgement. There is a wide range of optimisation models that aim to improve the outcome of network design decisions. However, their practical performance often remains unknown, as their implementation into the managerial decision process is largely neglected. Such theory-driven models usually focus on single aspects of the decision, without being able to accommodate the practical problem comprehensively. We employ the CIMO approach to resolve the issue and contribute by showing how an integration involving these methods can be useful for managers once the proper knowledge transfer has been effectuated. An innovative decision support framework, which combines mixed-integer linear programming, the Analytical Hierarchy Process, and the Pareto front is created and analysed during a case study in the med-tech industry. Results show that the framework accommodates managerial experience, integrates qualitative as well as quantitative criteria, and provides transparency over the entire range of efficient solutions. The framework and application results contribute towards the development of more flexible and easy-to-use decision support systems for GSCND.
AB - Integrating a broad range of information types and finding trade-offs between conflicting goals is a challenge in global supply chain network design (GSCND). Effective decision support systems (DSS) should be user-friendly, provide transparency, and support human judgement. There is a wide range of optimisation models that aim to improve the outcome of network design decisions. However, their practical performance often remains unknown, as their implementation into the managerial decision process is largely neglected. Such theory-driven models usually focus on single aspects of the decision, without being able to accommodate the practical problem comprehensively. We employ the CIMO approach to resolve the issue and contribute by showing how an integration involving these methods can be useful for managers once the proper knowledge transfer has been effectuated. An innovative decision support framework, which combines mixed-integer linear programming, the Analytical Hierarchy Process, and the Pareto front is created and analysed during a case study in the med-tech industry. Results show that the framework accommodates managerial experience, integrates qualitative as well as quantitative criteria, and provides transparency over the entire range of efficient solutions. The framework and application results contribute towards the development of more flexible and easy-to-use decision support systems for GSCND.
KW - Supply chain design
KW - Global supply chain
KW - Multi-criteria decision making
KW - Decision support systems
KW - Analytical hierarchy process
KW - Design science research
KW - Supply chain design
KW - Global supply chain
KW - Multi-criteria decision making
KW - Decision support systems
KW - Analytical hierarchy process
KW - Design science research
U2 - 10.1080/00207543.2020.1847341
DO - 10.1080/00207543.2020.1847341
M3 - Journal article
SN - 0020-7543
VL - 59
SP - 1557
EP - 1572
JO - International Journal of Production Research
JF - International Journal of Production Research
IS - 5
ER -