Large-scale group decision-making with uncertain and behavioral considerations: methods and applications
Introduction -- Uncertain Theory and Social Network Analysis -- Interval Type-2 Fuzzy Multi-criteria Decision-making -- Large-scale Group Decision-making with Uncertain Preferences -- Large-scale Group Decision-making with Social Relationships -- Consensus Study Considering Trust Relationships -- Co...
Gespeichert in:
| Hauptverfasser: | , |
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| Format: | Buch |
| Sprache: | English |
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Singapore
Springer
[2023]
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| Schriftenreihe: | Uncertainty and Operations Research
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| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Zusammenfassung: | Introduction -- Uncertain Theory and Social Network Analysis -- Interval Type-2 Fuzzy Multi-criteria Decision-making -- Large-scale Group Decision-making with Uncertain Preferences -- Large-scale Group Decision-making with Social Relationships -- Consensus Study Considering Trust Relationships -- Consensus Evolution Networks -- Consensus Reaching Process in Large-scale Group decision-making -- Application of LSGDM Methods in Group Recommendation -- Concluding Remarks. . This book investigates in detail large-scale group decision-making (LSGDM) problem, which has gradually evolved from the traditional group decision-making problem and has attracted more and more attention in the age of big data. Pursuing a holistic approach, the book establishes a fundamental framework for LSGDM with uncertain and behavioral considerations. To address the behavioral uncertainty and complexity of large groups of decision-makers, this book mainly focuses on new solutions of LSGDM problems using the interval type-2 fuzzy uncertainty theory and social network analysis techniques, including the exploration of uncertain clustering analysis, the consideration of social relationships, especially trust relationships, the construction of consensus evolution networks, etc. The book is intended for researchers and postgraduates who are interested in complex group decision-making in the new media era. Authors also investigate the similar features between LSGDM problems and group recommendations to study the applications of LSGDM methods. After reading this book, readers will have a new understanding of the LSGDM study under the real complicated context. |
| Beschreibung: | Literaturangaben |
| Beschreibung: | xi, 364 Seiten Illustrationen, Diagramme |
| ISBN: | 9789811981661 |
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| 520 | |a This book investigates in detail large-scale group decision-making (LSGDM) problem, which has gradually evolved from the traditional group decision-making problem and has attracted more and more attention in the age of big data. Pursuing a holistic approach, the book establishes a fundamental framework for LSGDM with uncertain and behavioral considerations. To address the behavioral uncertainty and complexity of large groups of decision-makers, this book mainly focuses on new solutions of LSGDM problems using the interval type-2 fuzzy uncertainty theory and social network analysis techniques, including the exploration of uncertain clustering analysis, the consideration of social relationships, especially trust relationships, the construction of consensus evolution networks, etc. The book is intended for researchers and postgraduates who are interested in complex group decision-making in the new media era. Authors also investigate the similar features between LSGDM problems and group recommendations to study the applications of LSGDM methods. After reading this book, readers will have a new understanding of the LSGDM study under the real complicated context. | ||
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Datensatz im Suchindex
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Contents 1 Introduction . 1.1 1.2 What is Large-Scale Group Decision-Making? . Literature Review Regarding Large-Scale Group Decision-Making. 3 References . 2 Uncertain Theory and Group Decision-Making . Interval Type-2 Fuzzy Sets. 2.1.1 Basic Concepts of IT2 FSs . 2.1.2 Distance and Similarity of IT2 FSs . 2.1.3 Aggregation Operators of IT2 FSs. 2.2 Group Decision-Making. 2.2.1 Fuzzy Preference Relation . 2.2.2 Traditional Consensus Reaching Models . 2.3 Decision Behavior Analysis. 2.3.1 Prospect Theory . 2.3.2 Social Network Analysis. 2.3.3 Trust Networks . References . 2.1 3 Interval Tÿpe-2 Fuzzy Decision-Making
. 3.1 3.2 3.3 Interval Type-2 Fuzzy Linguistic Variables. Interval Type-2 Fuzzy Multi-Criteria Decision-Making Methods . 3.2.1 Interval Type-2 Fuzzy ANP Method . 3.2.2 Interval Type-2 Fuzzy TOPSIS Method . An Interval Type-2 Fuzzy Quality Function Deployment Model . 3.3.1 Introduction of Quality Function Deployment. 3.3.2 Classify CRs Using Kano Model. 3.3.3 Determine the Weights for CRs Considering the Development Stages of Enterprises. 1 1 7 13 13 14 17 20 24 24 26 28 28 28 31 32 37 37 39 40 42 45 45 48 50 vii
viii Contents Rank the Priorities of DRs Using the Extended Linguistic TOPSIS Method. 3.3.5 The Proposed QFD Model and Its Application . 3.4 Dimension Reduction Analysis Based on Uncertain Preference Information. 67 3.4.1 Interval Type-2 Fuzzy Equivalence Relation Clustering Method . 3.4.2 Interval Туре—2 Fuzzy Principal Component Analysis. 70 3.5 Interval Type-2 Fuzzy Trust Computing . 3.5.1 Trust Degree Represented by IT2FSs . 3.5.2 Interval Type-2 Fuzzy Trust Propagation and Aggregation . 77 3.5.3 Interval Type-2 Fuzzy Trust Evaluation Model in S-Commerce. 80 3.5.4 Illustrative Example. References . 3.3.4 4 5 Large-Scale Group Decision-Making with Interval Туре—2 Fuzzy Preferences . 4.1 LSGDM Using Interval Type-2 Fuzzy Equivalence Relation Clustering Analysis Model. 91 4.1.1 Procedures of the IT2-FEC-Based LSGDM Method. 4.1.2 Numerical Example
. 4.2 LSGDM Using Interval Typc-2 Fuzzy Principal Component Analysis. 102 4.2.1 Attributes Reduction Using the IT2-PCA Model. 4.2.2 An E-Commerce Case Study for the IT2-PCA-Based LSGDM Model. 4.3 A Dynamic Programming Clustering Model for Interval Type-2 Fuzzy LSGDM Problems . 114 4.3.1 Description of the LSGDM Problems . 4.3.2 New Clustering Model Based on Dynamic ProgrammingAlgorithm. 4.3.3 New WeightDetermination Model . 4.3.4 New Ranking Method Based on the Centroids ofIT2FSs . 122 References . Interval Туре—2 Fuzzy Large-Scale Group Decision-Making Considering Social Relationships . 127 5.1 Main Ideas of Uncertain LSGDM Methods Considering Social Relationships . 127 52 56 68 74 76 81 85 91 91 96 102 105 115 117 120 124
Contents An Interval Type-2 Fuzzy TOPSIS Model for LSGDM with Social Network Information . 128 5.2.1 Community Detection of LSGDM. 5.2.2 Weights Determination for Individual Experts. 5.2.3 Partition Weights Determination . 5.2.4 The Solution for LSGDM Problems with Social Relationships . 5.2.5 Main Characteristics of the Proposed LSGDM Model. 5.3 An LSGDM Method Combining Internal Preference Information and External Social Network Structures. 134 5.3.1 Main Ideas of the Proposed LSGDM Method . 5.3.2 Combination of the Internal and External Information . 5.3.3 Community Detection with Hybrid Information . 5.3.4 Main Steps of the Proposed LSGDM Method . 5.3.5 Illustrative Exampleand Comparisons . References . ix 5.2 6 Social Trust Relationships in Group Decision-Making . CRP with the Implicit Trust Relationships . 6.1.1 Cost Consensus Models Based on the Implicit Trust Rlationships . 6.1.2 Modify the Adjustment Costs Considering the Trust Behavior . 166 6.1.3 Illustrative
Example. 6.1.4 Comparative Analysis . 6.2 Social Network Consensus with Uninorm Interval Trust Propagation . 174 6.2.1 Identification of Consensus Inconsistency . 6.2.2 Trust-Based Personalized Feedback Mechanism. 6.2.3 Personalized AdoptionCoefficient Based on Minimum Cost . 6.2.4 Comparison and Discussion . 6.3 Social Trust-Driven Consensus Considering Assessments-Modifications Willingness . 179 6.3.1 Social Trust Analysis. 6.3.2 Social Trust Driven Consensus Model with Minimum Adjustments. 6.3.3 Interactive Social Trust Driven Consensus Reaching Process . 187 References . 6.1 128 129 130 131 134 135 136 139 143 146 153 155 155 157 168 171 174 175 177 178 180 182 190
X 7 Contents Consensus Evolution Networks in Group Decision-Making . Consensus Evolution Networks. 7.1.1 Concept and Characteristics of CENs . 7.1.2 Consensus Measure Based on CENs. 7.1.3 Feedback Adjustment Process Based on CENs . 7.2 Consensus Evolution on Multiplex Networks Considering Trust Relationships . 208 7.2.1 Trust-Consensus Multiplex Networks . 7.2.2 Evolution of the Trust-Consensus Multiplex Networks . 7.2.3 Overall Consensus Level of the Evolved Trust-Consensus Multiplex Networks . 217 7.2.4 Main Procedures of the Proposed Consensus Evolution Model. 218 7.2.5 Illustrative Example. References . 7.1 8 193 193 193 198 203 208 214 220 228 Large-Scale Group Decision-Making Considering Trust Behavior . 231 An LSGDM Method Based on A Two-Stage Social Trust Partition Model . 231 8.1.1 The Shortest Path Algorithm for Trust Propagation . 8.1.2 Two-Stage Trust Network Partition Algorithm . 8.1.3 Weights
Determination with Trust Information . 8.1.4 Main Procedures and Characteristics of the LSGDM Model . 8.2 Non-cooperative Behavior Management in LSGDM with Trust Relationships. 242 8.2.1 Non-cooperative Behaviors Analysis and Management . 8.2.2 LSGDM Model Considering the Non-cooperative Behavior . 246 8.3 Social Network LSGDM Considering Voluntary Trust Loss . 8.3.1 Trust Cop-К-Means Clustering Analysis . 249 8.3.2 Improved Minimum-Cost Consensus Model Considering Voluntary TrustLoss . 8.3.3 Discussions and Comparative Analysis. References . 8.1 9 232 233 237 238 242 248 256 261 265 New Perspectives on Consensus Reaching Process in Large-Scale Group Decision-Making. 269 9.1 An LSGDM Method Balancing the Conflict Between CRP andDCAP . 269 9.1.1 The Dynamic Clustering Analysis Process 9.1.2 in LSGDM . The CRP in LSGDM Based on the DCAP . 270 276
Contents xi The Solution for LSGDM Balancing the DCAP and CRP. 279 9.1.4 Case Study . 9.2 A New Clustering Analysis Reducing the Complexity of CRP . 290 9.2.1 Motivation on the Clustering Analysis Considering Adjustment Costs . 9.2.2 A New Clustering Algorithm Considering Adjustment Costs . 9.2.3 Main Procedures of the Clustering Analysis for LSGDM. 9.2.4 A Case of Team Construction. References . 9.1.3 10 Application of LSGDM Methods. 10.1 283 290 291 298 299 308 311 312 312 LSGDM Model in Online-Customer Segmentation. 10.1.1 Online Evaluation Process . 10.1.2 Dynamic Online-Customer Segmentation with Semantic Evaluation Information . 10.2 A Social Commerce Purchasing Model with Trust Network and Item Review Information . 320 10.2.1 Motivation of Combining Trust Relationship and Item Review.
10.2.2 S-Commerce Purchasing Decision Model Based on User Trust and Item Review . 322 10.2.3 Inexperienced Purchasing Decision Based on the Composite Network Model. 329 10.2.4 Application . 10.3 LSGDM Model in Group Recommendation . 10.3.1 Data Selection. 10.3.2 Trust Network Construction with the “MovieLens-1 Μ” Dataset. 338 10.3.3 The Application of the Proposed Solution . 10.3.4 Comparison Analysis. 10.4 Social Recommendation with LSGDM for Cyber-Enabled Online Service . 347 10.4.1 Modeling of Scholarly Large-Scale Group Decision-Making Problem . 10.4.2 A Two-Stage LSGDM Solution for Social Recommendation . 350 10.4.3 Experiment and Analysis . References . 354 358 Concluding Remarks. 363 313 320 331 337 338 340 343 348 |
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| discipline | Wirtschaftswissenschaften |
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| id | DE-604.BV049813207 |
| illustrated | Illustrated |
| indexdate | 2024-11-11T09:10:43Z |
| institution | BVB |
| isbn | 9789811981661 |
| language | English |
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| series2 | Uncertainty and Operations Research |
| spelling | Wu, Tong Verfasser (DE-588)1258890631 aut Large-scale group decision-making with uncertain and behavioral considerations methods and applications Tong Wu, Xinwang Liu Singapore Springer [2023] © 2023 xi, 364 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Uncertainty and Operations Research Literaturangaben Introduction -- Uncertain Theory and Social Network Analysis -- Interval Type-2 Fuzzy Multi-criteria Decision-making -- Large-scale Group Decision-making with Uncertain Preferences -- Large-scale Group Decision-making with Social Relationships -- Consensus Study Considering Trust Relationships -- Consensus Evolution Networks -- Consensus Reaching Process in Large-scale Group decision-making -- Application of LSGDM Methods in Group Recommendation -- Concluding Remarks. . This book investigates in detail large-scale group decision-making (LSGDM) problem, which has gradually evolved from the traditional group decision-making problem and has attracted more and more attention in the age of big data. Pursuing a holistic approach, the book establishes a fundamental framework for LSGDM with uncertain and behavioral considerations. To address the behavioral uncertainty and complexity of large groups of decision-makers, this book mainly focuses on new solutions of LSGDM problems using the interval type-2 fuzzy uncertainty theory and social network analysis techniques, including the exploration of uncertain clustering analysis, the consideration of social relationships, especially trust relationships, the construction of consensus evolution networks, etc. The book is intended for researchers and postgraduates who are interested in complex group decision-making in the new media era. Authors also investigate the similar features between LSGDM problems and group recommendations to study the applications of LSGDM methods. After reading this book, readers will have a new understanding of the LSGDM study under the real complicated context. Operations research. Production management. Entscheidungsfindung (DE-588)4113446-1 gnd rswk-swf Operations Research (DE-588)4043586-6 gnd rswk-swf Large-scale Group Decision-making Interval Type-2 Fuzzy Sets Clustering Analysis Community Detection Consensus Reaching Process Group Recommendation Operations Research (DE-588)4043586-6 s Entscheidungsfindung (DE-588)4113446-1 s DE-604 Liu, Xinwang Verfasser (DE-588)1109798849 aut Äquivalent Druck-Ausgabe, Paperback 978-981-1981-69-2 Erscheint auch als Online-Ausgabe 978-981-19-8167-8 Digitalisierung UB Bamberg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=035153548&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Wu, Tong Liu, Xinwang Large-scale group decision-making with uncertain and behavioral considerations methods and applications Operations research. Production management. Entscheidungsfindung (DE-588)4113446-1 gnd Operations Research (DE-588)4043586-6 gnd |
| subject_GND | (DE-588)4113446-1 (DE-588)4043586-6 |
| title | Large-scale group decision-making with uncertain and behavioral considerations methods and applications |
| title_auth | Large-scale group decision-making with uncertain and behavioral considerations methods and applications |
| title_exact_search | Large-scale group decision-making with uncertain and behavioral considerations methods and applications |
| title_full | Large-scale group decision-making with uncertain and behavioral considerations methods and applications Tong Wu, Xinwang Liu |
| title_fullStr | Large-scale group decision-making with uncertain and behavioral considerations methods and applications Tong Wu, Xinwang Liu |
| title_full_unstemmed | Large-scale group decision-making with uncertain and behavioral considerations methods and applications Tong Wu, Xinwang Liu |
| title_short | Large-scale group decision-making with uncertain and behavioral considerations |
| title_sort | large scale group decision making with uncertain and behavioral considerations methods and applications |
| title_sub | methods and applications |
| topic | Operations research. Production management. Entscheidungsfindung (DE-588)4113446-1 gnd Operations Research (DE-588)4043586-6 gnd |
| topic_facet | Operations research. Production management. Entscheidungsfindung Operations Research |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=035153548&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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