A multi-structural framework for adaptive supply chain planning and operations control with structure dynamics considerations
Autor: | Joachim Kaeschel, Dmitry Ivanov, Boris Sokolov |
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Rok vydání: | 2010 |
Předmět: |
Information Systems and Management
Supply chain management Adaptive control General Computer Science business.industry Computer science Supply chain media_common.quotation_subject Service management Management Science and Operations Research Industrial engineering Industrial and Manufacturing Engineering Adaptability Conceptual framework Modeling and Simulation Added value business Supply chain optimization Simulation Agile software development media_common |
Zdroj: | European Journal of Operational Research. 200:409-420 |
ISSN: | 0377-2217 |
DOI: | 10.1016/j.ejor.2009.01.002 |
Popis: | A trend in up-to-date developments in supply chain management (SCM) is to make supply chains more agile, flexible, and responsive. In supply chains, different structures (functional, organizational, informational, financial, etc.) are (re)formed. These structures interrelate with each other and change in dynamics. The paper introduces a new conceptual framework for multi-structural planning and operations of adaptive supply chains with structure dynamics considerations. We elaborate a vision of adaptive supply chain management (A-SCM), a new dynamic model and tools for the planning and control of adaptive supply chains. SCM is addressed from perspectives of execution dynamics under uncertainty. Supply chains are modelled in terms of dynamic multi-structural macro-states, based on simultaneous consideration of the management as a function of both states and structures. The research approach is theoretically based on the combined application of control theory, operations research, and agent-based modelling. The findings suggest constructive ways to implement multi-structural supply chain management and to transit from a “one-way” partial optimization to the feedback-based, closed-loop adaptive supply chain optimization and execution management for value chain adaptability, stability and crisis-resistance. The proposed methodology enhances managerial insight into advanced supply chain management. |
Databáze: | OpenAIRE |
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