Multi-Criteria and Multi-Dimensional Analysis in Decisions
Decision Making with Preference Vector Methods (PVM) and Vector Measure Construction Methods (VMCM)
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Beschreibung
A new era is emerging in which a group of quantitative methods featuring characteristics of multidimensional comparative analysis (MCA) and multi-criteria decision-making analysis (MCDA) can be used to automate objective decision-making processes. This book introduces the character of the criteria (desirable, non-desirable, motivating, demotivating, and neutral) to MCDA and MCA methods. It presents the author’s own developed methods, the preference vector method (PVM), for solving multi-criteria problems in decision making; and, vector measure construction method (VMCM), which is dedicated to solving typical problems in the field of multidimensional comparative analysis. All methods are explained step by step with relevant examples, primarily in the fields of economics and management.
A new era is emerging in which a group of quantitative methods featuring characteristics of multidimensional comparative analysis (MCA) and multi-criteria decision-making analysis (MCDA) can be used to automate objective decision-making processes. This book introduces the character of the criteria (desirable, non-desirable, motivating, demotivating, and neutral) to MCDA and MCA methods. It presents the author’s own developed methods, the preference vector method (PVM), for solving multi-criteria problems in decision making; and, vector measure construction method (VMCM), which is dedicated to solving typical problems in the field of multidimensional comparative analysis. All methods are explained step by step with relevant examples, primarily in the fields of economics and management.
Features real-life examples from economics and management Presents similarities between MCA and MCDA methods in decision making Presents character criteria methods for decision making
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Themen in »Multi-Criteria and Multi-Dimensional Analysis in Decisions«
multi-criteria decision-making analysis (MCDA) vector measure construction method (VMCM) preference vector method (PVM) multidimensional comparative analysis (MCA) multiple criteria decision-making (MCDM)