Multiple-Criteria Decision-Making (MCDM) Techniques for Business Processes Information Management
Information management is a common paradigm in modern decision-making. A wide range of decision-making techniques have been proposed in the literature to model complex business and engineering processes. In this Special Issue, 16 selected and peer-reviewed original research articles contribute to bu...
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Other Authors: | , |
Format: | eBook |
Language: | English |
Published: |
MDPI - Multidisciplinary Digital Publishing Institute
2019
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Online Access: | |
Collection: | Directory of Open Access Books - Collection details see MPG.ReNa |
Summary: | Information management is a common paradigm in modern decision-making. A wide range of decision-making techniques have been proposed in the literature to model complex business and engineering processes. In this Special Issue, 16 selected and peer-reviewed original research articles contribute to business information management in various current real-world problems by proposing crisp or uncertain multiple-criteria decision-making (MCDM) models and techniques, mostly including multi-attribute decision-making (MADM) approaches, in addition to a single paper proposing an interactive multi-objective decision-making (MODM) approach. Particular attention is devoted to information aggregation operators; 65% of papers dealt with this item. The topics of this Special Issue gained attention in Europe and Asia. A total of 48 authors from seven countries contributed to this Issue. The papers are mainly concentrated in three application areas: supplier selection and rational order allocation, the evaluation and selection of goods or facilities, and personnel selection/partner selection. A number of new approaches are proposed that are expected to attract great interest from the research community. |
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Item Description: | Creative Commons (cc), https://creativecommons.org/licenses/by-nc-nd/4.0/ |
Physical Description: | 1 electronic resource (320 p.) |
ISBN: | books978-3-03897-643-1 9783038976424 |