Bibliometric Analyses in Data-Driven Decision-Making

• Autore: Chatterjee Prasenjit
• Pubblicazione: Newark : , : John Wiley & Sons, Incorporated, , 2025; ©2025
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (520 pages)
• Disciplina: 020.72/7
• Soggetto topico: Bibliometrics - Methodology; Bibliometrics
• Altri autori: SahaAbhijit KadrySeifedine DemirGulay
• Nota di contenuto: Preface xxiii -- Acknowledgements xxix -- Part 1: Introduction to Bibliometric Analysis and Methodologies 1 -- 1 Introduction to Bibliometric Analysis and Methodologies 3 Gülay Demir, Prasenjit Chatterjee, Abhijit Saha and Seifedine Kadry -- 1.1 Introduction 4 -- 1.1.1 Stages of Bibliometric Analysis 5 -- 1.1.1.1 Preparation Phase Before Bibliometric Analysis 6 -- 1.1.1.2 Application Phase of Bibliometric Analysis 14 -- 1.2 Historical Development of Bibliometrics 21 -- 1.3 Key Bibliometric Indicators 24 -- 1.4 Bibliometric Data Sources 26 -- 1.5 Methodologies in Bibliometric Analysis 29 -- 1.6 Applications of Bibliometric Analysis 31 -- 1.7 Challenges and Limitations 33 -- 1.8 Future Directions in Bibliometrics 35 -- 1.9 Conclusions 38 -- References 39 -- Part 2: Bibliometric Analysis in Logistics and Supply Chain 45 -- 2 Multi-Criteria Decision-Making in Logistics and Supply Chain Management: A Bibliometric Analysis 47 Murat Kemal Keleş and Askin Ozdagoglu -- 2.1 Introduction 48 -- 2.2 Literature Review 51 -- 2.3 Materials and Methods 52 -- 2.4 Bibliometric Analysis Results of the Logistics/Supply Chain and MCDM 53 -- 2.4.1 Performance Analysis 53 -- 2.4.1.1 The General Overview of the Database 53 -- 2.4.1.2 The Annual Publication and Citation Status 54 -- 2.4.1.3 The Publication and Citation Status of Journals 55 -- 2.4.1.4 The Most Relevant Affiliations 55 -- 2.4.1.5 Authors’ Status 57 -- 2.4.1.6 The Most Productive Countries 57 -- 2.4.1.7 Most Cited Document 59 -- 2.4.2 Scientific Mapping Analysis 60 -- 2.4.2.1 Thematic Map 60 -- 2.4.2.2 Trend Topics 61 -- 2.4.2.3 Keyword Analysis 62 -- 2.5 Discussion 64 -- 2.6 Conclusions 66 -- References 67 -- 3 Digital Supply Chain: A Bibliometric Analysis 71 Rajeev Ranjan, Sonu Rajak, Prasenjit Chatterjee, Gulay Demir and Ernesto DR Santibanez Gonzalez -- 3.1 Introduction 72 -- 3.2 Bibliometric Analysis 74 -- 3.2.1 Research Gaps and Research Questions 75 -- 3.3 Materials and Methods 76 -- 3.4 Bibliometric Analysis of DSC 79 -- 3.4.1 Performance Analysis 79 -- 3.4.1.1 Overall Review of the Database 79 -- 3.4.1.2 A Rise in Annual Publications 80 -- 3.4.1.3 Average Annual Citations 81 -- 3.4.1.4 Sankey Diagram 81 -- 3.4.1.5 Most Cited and Most Published Journals 83 -- 3.4.1.6 The Most Important Affiliations 83 -- 3.4.1.7 Frequently Referenced Authors 84 -- 3.4.1.8 The Most Productive Countries 84 -- 3.4.1.9 Most Cited Document 86 -- 3.4.2 Analysis of Science Mapping 88 -- 3.4.2.1 Thematic Map 88 -- 3.4.2.2 Trend Topics 89 -- 3.4.2.3 Word Cloud 90 -- 3.4.2.4 Collaborative Network of Co-Words in Publications on DSC 91 -- 3.4.2.5 Conceptual Structure Map 92 -- 3.5 Discussions 92 -- 3.6 Conclusions 94 -- References 95 -- 4 Agile Supply Chain Dynamics: A Bibliometric Analysis with a Technology-Barrier-Performance Framework 99 Vikrant Sharma and Prasenjit Chatterjee -- 4.1 Introduction 100 -- 4.2 Literature Review 101 -- 4.3 Methodology 103 -- 4.4 Results 104 -- 4.4.1 Descriptive Analysis 104 -- 4.4.2 Sources 106 -- 4.4.3 Authors 108 -- 4.4.4 Main Research Country 110 -- 4.4.5 Relationship 112 -- 4.5 Mapping Results with VOSviewer Software 112 -- 4.6 Conceptual Structure and Evolution of the Field 115 -- 4.7 Discussion 122 -- 4.7.1 Principal Findings 122 -- 4.7.2 Technology, Enablers, Barriers, and Performance Indicators Framework 124 -- 4.7.3 Future Direction for Agile Supply Chain 127 -- 4.7.4 Limitation of Study 128 -- 4.8 Conclusions 128 -- References 129 -- Part 3: Multi-Criteria Decision‐Making (MCDM) and Bibliometric Analysis 137 -- 5 Multi-Criteria Decision-Making Methods for Robot Selection: A Bibliometric Analysis of Research Trends 139 Rajeev Ranjan, Sonu Rajak and Prasenjit Chatterjee -- 5.1 Introduction 140 -- 5.2 Bibliometric Analysis 142 -- 5.3 Materials and Methods 143 -- 5.4 Results 146 -- 5.4.1 Performance Analysis 146 -- 5.4.1.1 Database Overview 147 -- 5.4.1.2 Annual Increase in Publications 147 -- 5.4.1.3 Status of Average Annual Citations 148 -- 5.4.1.4 Sankey Diagram 149 -- 5.4.1.5 Most Cited Journals 149 -- 5.4.1.6 The Most Relevant Affiliations 151 -- 5.4.1.7 The Most Cited Authors 151 -- 5.4.1.8 The Most Productive Nations 152 -- 5.4.1.9 Most Cited Document 155 -- 5.4.2 Science Mapping Analysis 155 -- 5.4.2.1 Co-Occurrence Keywords Analysis 155 -- 5.4.2.2 Thematic Analysis 158 -- 5.4.2.3 Trend Topics 159 -- 5.4.2.4 Scientific Landscape 160 -- 5.4.2.5 Timeline Analysis 161 -- 5.4.2.6 Citation Burst Analysis 163 -- 5.5 Discussion 163 -- 5.6 Conclusions, Managerial Implication, and Future Research Directions 165 -- References 166 -- 6 Bibliometrics Analysis on Economics and MCDM 169 Yüksel Aydın -- 6.1 Introduction 170 -- 6.2 Literature Review 171 -- 6.3 Research Methodology 174 -- 6.4 Bibliometric Analysis Results on Economics and MCDM 174 -- 6.4.1 Performance Analysis 174 -- 6.4.1.1 Main Information 174 -- 6.4.1.2 Annual Status of Publications 175 -- 6.4.1.3 Average Annual Citations 176 -- 6.4.1.4 Magazines with the Most Publications 176 -- 6.4.1.5 Most Important Universities 177 -- 6.4.1.6 Most Important Authors 178 -- 6.4.1.7 Most Productive Countries 179 -- 6.4.1.8 Most Cited Article 180 -- 6.4.2 Scientific Mapping Analysis 181 -- 6.4.2.1 Thematic Map 181 -- 6.4.2.2 Trend Topics 182 -- 6.4.2.3 Keyword Analysis 183 -- 6.5 Discussion 185 -- 6.6 Conclusion 186 -- References 187 -- 7 Material Selection by Multi-Criteria Decision-Making: A Bibliometric Analysis 191 Rajeev Ranjan, Sonu Rajak and Prasenjit Chatterjee -- 7.1 Introduction 192 -- 7.2 A Brief Background of Multi-Criteria Decision-Making (mcdm) 192 -- 7.2.1 Bibliometric Analysis 196 -- 7.2.2 Research Gaps and Research Questions 197 -- 7.3 Materials and Methods 198 -- 7.4 Material Selection by MCDM Method’s Bibliometric Analysis Findings 199 -- 7.4.1 Performance Analysis 199 -- 7.4.1.1 Overall Review of the Database 200 -- 7.4.1.2 An Increase in Publications Per Year 201 -- 7.4.1.3 Average Annual Citations 201 -- 7.4.1.4 Sankey Diagram 203 -- 7.4.1.5 Most Cited and Most Published Journals 203 -- 7.4.1.6 The Most Important Affiliations 204 -- 7.4.1.7 Frequently Referenced Authors 205 -- 7.4.1.8 The Most Productive Countries 205 -- 7.4.1.9 Most Cited Document 208 -- 7.4.2 Analysis of Science Mapping 208 -- 7.4.2.1 Thematic Map 209 -- 7.4.2.2 Trend Topics 210 -- 7.4.2.3 Keyword Co-Occurrence Analysis 212 -- 7.4.2.4 Scientific Landscape 213 -- 7.4.2.5 Timeline Analysis 214 -- 7.4.2.6 Citation Burst Analysis 216 -- 7.5 Discussions 216 -- 7.6 Conclusions, Managerial Implication, and Future Research Directions 218 -- References 220 -- 8 Evaluation Based on Distance from Average Solution (EDAS) Method: A Bibliometric Analysis 223 Rajeev Ranjan, Sonu Rajak, Prasenjit Chatterjee and Seifedine Kadry -- 8.1 Introduction 224 -- 8.2 EDAS Method 226 -- 8.2.1 Fundamentals of EDAS Method 226 -- 8.2.2 Bibliometric Analysis 229 -- 8.2.3 Research Gaps and Research Questions 230 -- 8.3 Materials and Methods 232 -- 8.4 Results of the EDAS Method Bibliometric Analysis 234 -- 8.4.1 Performance Analysis 234 -- 8.4.1.1 Overall Review of the Database 234 -- 8.4.1.2 Annual Publication Increase 235 -- 8.4.1.3 Average Annual Citations 235 -- 8.4.1.4 Sankey Diagram 237 -- 8.4.1.5 Most Cited and Most Published Journals 237 -- 8.4.1.6 The Affiliations that Matter Most 238 -- 8.4.1.7 Frequently Cited Authors 238 -- 8.4.1.8 The Most Productive Countries 239 -- 8.4.1.9 Most Cited Document 242 -- 8.4.2 Analysis of Science Mapping 243 -- 8.4.2.1 Thematic Map 243 -- 8.4.2.2 Trend Topics 243 -- 8.4.2.3 Keyword Co-Occurrence Analysis 245 -- 8.4.2.4 Scientific Landscape 247 -- 8.4.2.5 Timeline Analysis 248 -- 8.4.2.6 Citation Burst Analysis 249 -- 8.5 Discussions 250 -- 8.6 Conclusions 251 -- References 252 -- 9 Evolution of m-Polar Fuzzy Set as a Decision-Making Tool: A Bibliometric Review 257 Madan Jagtap and Prasad Karande -- 9.1 Introduction 258 -- 9.1.1 Paper Organization 259 -- 9.1.2 Research Methodology and Contributions of the Work 259 -- 9.2 Literature Review 261 -- 9.2.1 Different Types of Fuzzy Sets 261 -- 9.3 Fuzzy Sets in Decision-Making 262 -- 9.4 m-Polar Fuzzy Sets in Decision-Making 263 -- 9.5 Comparison of m-Polar Fuzzy Set and Ordinary Fuzzy Sets in Decision-Making 265 -- 9.6 Analysis of m-Polar FSs 265 -- 9.6.1 Analysis Based on m-Polar FS Publications 265 -- 9.6.2 Analysis Based on Journals 267 -- 9.6.3 Analysis Based on Authors’ Contributions 282 -- 9.6.4 Analysis Based on Application of m-Polar Fuzzy Logic 284 -- 9.6.5 Bibliometric Analysis for the m-Polar Fuzzy Set 286 -- 9.6.5.1 Co-Author and Author Mapping for m-Polar Fuzzy Set 286 -- 9.6.5.2 Bibliographic Coupling of Universities for the m-Polar Fuzzy Set 287 -- 9.6.5.3 Bibliographic Coupling Countries for the m-Polar Fuzzy Set 287 -- 9.6.5.4 Citation Documents Analysis for m-Polar Fuzzy Sets 288 -- 9.6.5.5 Co-Occurrences of Author’s Keywords Analysis for m-Polar Fuzzy Sets 289 -- 9.6.5.6 Co-Authorship Organizations Analysis for the m-Polar Fuzzy Sets 290 -- 9.7 Conclusion 290 -- ...
• Sommario/riassunto: The book provides essential insights and practical tools needed to effectively navigate the evolving landscape of scholarly research, helping enhance the understanding of publication trends, citation impacts, and collaboration networks across multiple fields. Bibliometric Analyses in Data-Driven Decision-Making offers a comprehensive guide to researchers, academics, and practitioners interested in utilizing bibliometric analysis to understand and navigate the dynamic landscape of the increasingly vital field of data-driven decision-making and its applications across many areas. It provides insights into growth, impact, and trends within the field, using bibliometric tools and methodologies. This volume adopts a pragmatic approach, balancing theoretical concepts with practical applications of data-driven decision-making models through the perspectives of bibliometric analyses using real-world examples, case studies, and step-by-step guides. The reader will find the book: Gives practical guidance on conducting bibliometric analyses across a range of applications for data-driven decision-making; Illustrates the application of bibliometric tools in the field with real-world case studies; Provides in-depth coverage of various bibliometric indicators and metrics; Explores emerging trends and challenges in bibliometric analysis; Provides a comprehensive overview of software and tools available for bibliometric research. Audience Librarians and Information professionals involved in research management, knowledge discovery, and the evaluation of scholarly communication, as well as professionals in industries reliant on cutting-edge research and development, technology assessment, and innovation. Also, a range of researchers and scholars seeking how to apply bibliometric analysis to assess the impact of their work, and advanced insights into bibliometric metrics, collaboration networks, and research trends.
• Titolo autorizzato: Bibliometric Analyses in Data-Driven Decision-Making
• ISBN: 1-394-30256-8; 1-394-30258-4; 1-394-30254-1
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9911019109403321
• Lo trovi qui: Univ. Federico II
• Serie: Sustainable Computing and Optimization Series