Identifying critical factors in systems with interrelated components: a method considering heterogeneous influence and strength attenuation

DOI10.1016/j.ejor.2022.02.012OpenAlexW4210897967MaRDI QIDQ2673592

Guozhu Jia, Qun Wang, Wen-Yan Song

Publication date: 10 June 2022

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2022.02.012

zbMATH Keywords

problem structuringattenuation effectpositive and negative influencesidentification of critical factorssmart home service

Mathematics Subject Classification ID

Decision theory (91B06) Management decision making, including multiple objectives (90B50) Case-oriented studies in operations research (90B90)

Cites Work

• Unnamed Item
• An intelligent decomposition of pairwise comparison matrices for large-scale decisions
• Generalized analytic network process
• Using multiple reference levels in multi-criteria decision aid: the generalized-additive independence model and the Choquet integral approaches
• Supply chain performance evaluation with data envelopment analysis and balanced scorecard approach
• Modelling multicriteria value interactions with reasoning maps
• Rationalising the use of twitter by official organisations during risk events: operationalising the social amplification of risk framework through causal loop diagrams
• Urban blight remediation strategies subject to seasonal constraints
• An algorithm for ranking the nodes of an urban network based on the concept of PageRank vector
• Analytic network process: an overview of applications
• Qualitative operators for reasoning maps: Evaluating multi-criteria options with networks of reasons
• Theory of capacities
• On the Theory of Scales of Measurement
• Causal maps and the evaluation of decision options—a review
• Reasoning maps for decision aid: an integrated approach for problem-structuring and multi-criteria evaluation

This page was built for publication: Identifying critical factors in systems with interrelated components: a method considering heterogeneous influence and strength attenuation