{"product_id":"bibliometric-analyses-in-data-driven-decision-making-hardback-9781394302529","title":"Bibliometric Analyses in Data-Driven Decision-Making (Hardback) 9781394302529","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eBibliometric Analyses in Data-Driven Decision-Making\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cfont size=\"4\"\u003ePrasenjit Chatterjee (Edited by), Chatterjee (Author), Abhijit Saha (Edited by), Seifedine Kadry (Edited by), Gulay Demir (Edited by)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781394302529, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 14 August 2025\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e720 pages\u003cbr\u003e28 x 19 x 2.5 cm, 1.225 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e\u003cb\u003eThe 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.\u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003e\u003ci\u003eBibliometric Analyses in Data-Driven Decision-Making\u003c\/i\u003e 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. \u003c\/p\u003e\n\u003cp\u003eThe reader will find the book: \u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eGives practical guidance on conducting bibliometric analyses across a range of applications for data-driven decision-making;\u003c\/li\u003e \u003cli\u003eIllustrates the application of bibliometric tools in the field with real-world case studies;\u003c\/li\u003e \u003cli\u003eProvides in-depth coverage of various bibliometric indicators and metrics;\u003c\/li\u003e \u003cli\u003eExplores emerging trends and challenges in bibliometric analysis;\u003c\/li\u003e \u003cli\u003eProvides a comprehensive overview of software and tools available for bibliometric research.\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003e\u003cb\u003eAudience\u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003eLibrarians 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.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003ePreface xxiii\u003c\/p\u003e \u003cp\u003eAcknowledgements xxix\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 1: Introduction to Bibliometric Analysis and Methodologies 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction to Bibliometric Analysis and Methodologies 3\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eGülay Demir, Prasenjit Chatterjee, Abhijit Saha and Seifedine Kadry\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 4\u003c\/p\u003e \u003cp\u003e1.1.1 Stages of Bibliometric Analysis 5\u003c\/p\u003e \u003cp\u003e1.1.1.1 Preparation Phase Before Bibliometric Analysis 6\u003c\/p\u003e \u003cp\u003e1.1.1.2 Application Phase of Bibliometric Analysis 14\u003c\/p\u003e \u003cp\u003e1.2 Historical Development of Bibliometrics 21\u003c\/p\u003e \u003cp\u003e1.3 Key Bibliometric Indicators 24\u003c\/p\u003e \u003cp\u003e1.4 Bibliometric Data Sources 26\u003c\/p\u003e \u003cp\u003e1.5 Methodologies in Bibliometric Analysis 29\u003c\/p\u003e \u003cp\u003e1.6 Applications of Bibliometric Analysis 31\u003c\/p\u003e \u003cp\u003e1.7 Challenges and Limitations 33\u003c\/p\u003e \u003cp\u003e1.8 Future Directions in Bibliometrics 35\u003c\/p\u003e \u003cp\u003e1.9 Conclusions 38\u003c\/p\u003e \u003cp\u003eReferences 39\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 2: Bibliometric Analysis in Logistics and Supply Chain 45\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Multi-Criteria Decision-Making in Logistics and Supply Chain Management: A Bibliometric Analysis 47\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMurat Kemal Keleş and Askin Ozdagoglu\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 48\u003c\/p\u003e \u003cp\u003e2.2 Literature Review 51\u003c\/p\u003e \u003cp\u003e2.3 Materials and Methods 52\u003c\/p\u003e \u003cp\u003e2.4 Bibliometric Analysis Results of the Logistics\/Supply Chain and MCDM 53\u003c\/p\u003e \u003cp\u003e2.4.1 Performance Analysis 53\u003c\/p\u003e \u003cp\u003e2.4.1.1 The General Overview of the Database 53\u003c\/p\u003e \u003cp\u003e2.4.1.2 The Annual Publication and Citation Status 54\u003c\/p\u003e \u003cp\u003e2.4.1.3 The Publication and Citation Status of Journals 55\u003c\/p\u003e \u003cp\u003e2.4.1.4 The Most Relevant Affiliations 55\u003c\/p\u003e \u003cp\u003e2.4.1.5 Authors’ Status 57\u003c\/p\u003e \u003cp\u003e2.4.1.6 The Most Productive Countries 57\u003c\/p\u003e \u003cp\u003e2.4.1.7 Most Cited Document 59\u003c\/p\u003e \u003cp\u003e2.4.2 Scientific Mapping Analysis 60\u003c\/p\u003e \u003cp\u003e2.4.2.1 Thematic Map 60\u003c\/p\u003e \u003cp\u003e2.4.2.2 Trend Topics 61\u003c\/p\u003e \u003cp\u003e2.4.2.3 Keyword Analysis 62\u003c\/p\u003e \u003cp\u003e2.5 Discussion 64\u003c\/p\u003e \u003cp\u003e2.6 Conclusions 66\u003c\/p\u003e \u003cp\u003eReferences 67\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Digital Supply Chain: A Bibliometric Analysis 71\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eRajeev Ranjan, Sonu Rajak, Prasenjit Chatterjee, Gulay Demir and Ernesto DR Santibanez Gonzalez\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 72\u003c\/p\u003e \u003cp\u003e3.2 Bibliometric Analysis 74\u003c\/p\u003e \u003cp\u003e3.2.1 Research Gaps and Research Questions 75\u003c\/p\u003e \u003cp\u003e3.3 Materials and Methods 76\u003c\/p\u003e \u003cp\u003e3.4 Bibliometric Analysis of DSC 79\u003c\/p\u003e \u003cp\u003e3.4.1 Performance Analysis 79\u003c\/p\u003e \u003cp\u003e3.4.1.1 Overall Review of the Database 79\u003c\/p\u003e \u003cp\u003e3.4.1.2 A Rise in Annual Publications 80\u003c\/p\u003e \u003cp\u003e3.4.1.3 Average Annual Citations 81\u003c\/p\u003e \u003cp\u003e3.4.1.4 Sankey Diagram 81\u003c\/p\u003e \u003cp\u003e3.4.1.5 Most Cited and Most Published Journals 83\u003c\/p\u003e \u003cp\u003e3.4.1.6 The Most Important Affiliations 83\u003c\/p\u003e \u003cp\u003e3.4.1.7 Frequently Referenced Authors 84\u003c\/p\u003e \u003cp\u003e3.4.1.8 The Most Productive Countries 84\u003c\/p\u003e \u003cp\u003e3.4.1.9 Most Cited Document 86\u003c\/p\u003e \u003cp\u003e3.4.2 Analysis of Science Mapping 88\u003c\/p\u003e \u003cp\u003e3.4.2.1 Thematic Map 88\u003c\/p\u003e \u003cp\u003e3.4.2.2 Trend Topics 89\u003c\/p\u003e \u003cp\u003e3.4.2.3 Word Cloud 90\u003c\/p\u003e \u003cp\u003e3.4.2.4 Collaborative Network of Co-Words in Publications on DSC 91\u003c\/p\u003e \u003cp\u003e3.4.2.5 Conceptual Structure Map 92\u003c\/p\u003e \u003cp\u003e3.5 Discussions 92\u003c\/p\u003e \u003cp\u003e3.6 Conclusions 94\u003c\/p\u003e \u003cp\u003eReferences 95\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Agile Supply Chain Dynamics: A Bibliometric Analysis with a Technology-Barrier-Performance Framework 99\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eVikrant Sharma and Prasenjit Chatterjee\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 100\u003c\/p\u003e \u003cp\u003e4.2 Literature Review 101\u003c\/p\u003e \u003cp\u003e4.3 Methodology 103\u003c\/p\u003e \u003cp\u003e4.4 Results 104\u003c\/p\u003e \u003cp\u003e4.4.1 Descriptive Analysis 104\u003c\/p\u003e \u003cp\u003e4.4.2 Sources 106\u003c\/p\u003e \u003cp\u003e4.4.3 Authors 108\u003c\/p\u003e \u003cp\u003e4.4.4 Main Research Country 110\u003c\/p\u003e \u003cp\u003e4.4.5 Relationship 112\u003c\/p\u003e \u003cp\u003e4.5 Mapping Results with VOSviewer Software 112\u003c\/p\u003e \u003cp\u003e4.6 Conceptual Structure and Evolution of the Field 115\u003c\/p\u003e \u003cp\u003e4.7 Discussion 122\u003c\/p\u003e \u003cp\u003e4.7.1 Principal Findings 122\u003c\/p\u003e \u003cp\u003e4.7.2 Technology, Enablers, Barriers, and Performance Indicators Framework 124\u003c\/p\u003e \u003cp\u003e4.7.3 Future Direction for Agile Supply Chain 127\u003c\/p\u003e \u003cp\u003e4.7.4 Limitation of Study 128\u003c\/p\u003e \u003cp\u003e4.8 Conclusions 128\u003c\/p\u003e \u003cp\u003eReferences 129\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 3: Multi-Criteria Decision‐Making (MCDM) and Bibliometric Analysis 137\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Multi-Criteria Decision-Making Methods for Robot Selection: A Bibliometric Analysis of Research Trends 139\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eRajeev Ranjan, Sonu Rajak and Prasenjit Chatterjee\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 140\u003c\/p\u003e \u003cp\u003e5.2 Bibliometric Analysis 142\u003c\/p\u003e \u003cp\u003e5.3 Materials and Methods 143\u003c\/p\u003e \u003cp\u003e5.4 Results 146\u003c\/p\u003e \u003cp\u003e5.4.1 Performance Analysis 146\u003c\/p\u003e \u003cp\u003e5.4.1.1 Database Overview 147\u003c\/p\u003e \u003cp\u003e5.4.1.2 Annual Increase in Publications 147\u003c\/p\u003e \u003cp\u003e5.4.1.3 Status of Average Annual Citations 148\u003c\/p\u003e \u003cp\u003e5.4.1.4 Sankey Diagram 149\u003c\/p\u003e \u003cp\u003e5.4.1.5 Most Cited Journals 149\u003c\/p\u003e \u003cp\u003e5.4.1.6 The Most Relevant Affiliations 151\u003c\/p\u003e \u003cp\u003e5.4.1.7 The Most Cited Authors 151\u003c\/p\u003e \u003cp\u003e5.4.1.8 The Most Productive Nations 152\u003c\/p\u003e \u003cp\u003e5.4.1.9 Most Cited Document 155\u003c\/p\u003e \u003cp\u003e5.4.2 Science Mapping Analysis 155\u003c\/p\u003e \u003cp\u003e5.4.2.1 Co-Occurrence Keywords Analysis 155\u003c\/p\u003e \u003cp\u003e5.4.2.2 Thematic Analysis 158\u003c\/p\u003e \u003cp\u003e5.4.2.3 Trend Topics 159\u003c\/p\u003e \u003cp\u003e5.4.2.4 Scientific Landscape 160\u003c\/p\u003e \u003cp\u003e5.4.2.5 Timeline Analysis 161\u003c\/p\u003e \u003cp\u003e5.4.2.6 Citation Burst Analysis 163\u003c\/p\u003e \u003cp\u003e5.5 Discussion 163\u003c\/p\u003e \u003cp\u003e5.6 Conclusions, Managerial Implication, and Future Research Directions 165\u003c\/p\u003e \u003cp\u003eReferences 166\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Bibliometrics Analysis on Economics and MCDM 169\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eYüksel Aydın\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 170\u003c\/p\u003e \u003cp\u003e6.2 Literature Review 171\u003c\/p\u003e \u003cp\u003e6.3 Research Methodology 174\u003c\/p\u003e \u003cp\u003e6.4 Bibliometric Analysis Results on Economics and MCDM 174\u003c\/p\u003e \u003cp\u003e6.4.1 Performance Analysis 174\u003c\/p\u003e \u003cp\u003e6.4.1.1 Main Information 174\u003c\/p\u003e \u003cp\u003e6.4.1.2 Annual Status of Publications 175\u003c\/p\u003e \u003cp\u003e6.4.1.3 Average Annual Citations 176\u003c\/p\u003e \u003cp\u003e6.4.1.4 Magazines with the Most Publications 176\u003c\/p\u003e \u003cp\u003e6.4.1.5 Most Important Universities 177\u003c\/p\u003e \u003cp\u003e6.4.1.6 Most Important Authors 178\u003c\/p\u003e \u003cp\u003e6.4.1.7 Most Productive Countries 179\u003c\/p\u003e \u003cp\u003e6.4.1.8 Most Cited Article 180\u003c\/p\u003e \u003cp\u003e6.4.2 Scientific Mapping Analysis 181\u003c\/p\u003e \u003cp\u003e6.4.2.1 Thematic Map 181\u003c\/p\u003e \u003cp\u003e6.4.2.2 Trend Topics 182\u003c\/p\u003e \u003cp\u003e6.4.2.3 Keyword Analysis 183\u003c\/p\u003e \u003cp\u003e6.5 Discussion 185\u003c\/p\u003e \u003cp\u003e6.6 Conclusion 186\u003c\/p\u003e \u003cp\u003eReferences 187\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Material Selection by Multi-Criteria Decision-Making: A Bibliometric Analysis 191\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eRajeev Ranjan, Sonu Rajak and Prasenjit Chatterjee\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 192\u003c\/p\u003e \u003cp\u003e7.2 A Brief Background of Multi-Criteria Decision-Making (mcdm) 192\u003c\/p\u003e \u003cp\u003e7.2.1 Bibliometric Analysis 196\u003c\/p\u003e \u003cp\u003e7.2.2 Research Gaps and Research Questions 197\u003c\/p\u003e \u003cp\u003e7.3 Materials and Methods 198\u003c\/p\u003e \u003cp\u003e7.4 Material Selection by MCDM Method’s Bibliometric Analysis Findings 199\u003c\/p\u003e \u003cp\u003e7.4.1 Performance Analysis 199\u003c\/p\u003e \u003cp\u003e7.4.1.1 Overall Review of the Database 200\u003c\/p\u003e \u003cp\u003e7.4.1.2 An Increase in Publications Per Year 201\u003c\/p\u003e \u003cp\u003e7.4.1.3 Average Annual Citations 201\u003c\/p\u003e \u003cp\u003e7.4.1.4 Sankey Diagram 203\u003c\/p\u003e \u003cp\u003e7.4.1.5 Most Cited and Most Published Journals 203\u003c\/p\u003e \u003cp\u003e7.4.1.6 The Most Important Affiliations 204\u003c\/p\u003e \u003cp\u003e7.4.1.7 Frequently Referenced Authors 205\u003c\/p\u003e \u003cp\u003e7.4.1.8 The Most Productive Countries 205\u003c\/p\u003e \u003cp\u003e7.4.1.9 Most Cited Document 208\u003c\/p\u003e \u003cp\u003e7.4.2 Analysis of Science Mapping 208\u003c\/p\u003e \u003cp\u003e7.4.2.1 Thematic Map 209\u003c\/p\u003e \u003cp\u003e7.4.2.2 Trend Topics 210\u003c\/p\u003e \u003cp\u003e7.4.2.3 Keyword Co-Occurrence Analysis 212\u003c\/p\u003e \u003cp\u003e7.4.2.4 Scientific Landscape 213\u003c\/p\u003e \u003cp\u003e7.4.2.5 Timeline Analysis 214\u003c\/p\u003e \u003cp\u003e7.4.2.6 Citation Burst Analysis 216\u003c\/p\u003e \u003cp\u003e7.5 Discussions 216\u003c\/p\u003e \u003cp\u003e7.6 Conclusions, Managerial Implication, and Future Research Directions 218\u003c\/p\u003e \u003cp\u003eReferences 220\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Evaluation Based on Distance from Average Solution (EDAS) Method: A Bibliometric Analysis 223\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eRajeev Ranjan, Sonu Rajak, Prasenjit Chatterjee and Seifedine Kadry\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 224\u003c\/p\u003e \u003cp\u003e8.2 EDAS Method 226\u003c\/p\u003e \u003cp\u003e8.2.1 Fundamentals of EDAS Method 226\u003c\/p\u003e \u003cp\u003e8.2.2 Bibliometric Analysis 229\u003c\/p\u003e \u003cp\u003e8.2.3 Research Gaps and Research Questions 230\u003c\/p\u003e \u003cp\u003e8.3 Materials and Methods 232\u003c\/p\u003e \u003cp\u003e8.4 Results of the EDAS Method Bibliometric Analysis 234\u003c\/p\u003e \u003cp\u003e8.4.1 Performance Analysis 234\u003c\/p\u003e \u003cp\u003e8.4.1.1 Overall Review of the Database 234\u003c\/p\u003e \u003cp\u003e8.4.1.2 Annual Publication Increase 235\u003c\/p\u003e \u003cp\u003e8.4.1.3 Average Annual Citations 235\u003c\/p\u003e \u003cp\u003e8.4.1.4 Sankey Diagram 237\u003c\/p\u003e \u003cp\u003e8.4.1.5 Most Cited and Most Published Journals 237\u003c\/p\u003e \u003cp\u003e8.4.1.6 The Affiliations that Matter Most 238\u003c\/p\u003e \u003cp\u003e8.4.1.7 Frequently Cited Authors 238\u003c\/p\u003e \u003cp\u003e8.4.1.8 The Most Productive Countries 239\u003c\/p\u003e \u003cp\u003e8.4.1.9 Most Cited Document 242\u003c\/p\u003e \u003cp\u003e8.4.2 Analysis of Science Mapping 243\u003c\/p\u003e \u003cp\u003e8.4.2.1 Thematic Map 243\u003c\/p\u003e \u003cp\u003e8.4.2.2 Trend Topics 243\u003c\/p\u003e \u003cp\u003e8.4.2.3 Keyword Co-Occurrence Analysis 245\u003c\/p\u003e \u003cp\u003e8.4.2.4 Scientific Landscape 247\u003c\/p\u003e \u003cp\u003e8.4.2.5 Timeline Analysis 248\u003c\/p\u003e \u003cp\u003e8.4.2.6 Citation Burst Analysis 249\u003c\/p\u003e \u003cp\u003e8.5 Discussions 250\u003c\/p\u003e \u003cp\u003e8.6 Conclusions 251\u003c\/p\u003e \u003cp\u003eReferences 252\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Evolution of m-Polar Fuzzy Set as a Decision-Making Tool: A Bibliometric Review 257\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMadan Jagtap and Prasad Karande\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 258\u003c\/p\u003e \u003cp\u003e9.1.1 Paper Organization 259\u003c\/p\u003e \u003cp\u003e9.1.2 Research Methodology and Contributions of the Work 259\u003c\/p\u003e \u003cp\u003e9.2 Literature Review 261\u003c\/p\u003e \u003cp\u003e9.2.1 Different Types of Fuzzy Sets 261\u003c\/p\u003e \u003cp\u003e9.3 Fuzzy Sets in Decision-Making 262\u003c\/p\u003e \u003cp\u003e9.4 m-Polar Fuzzy Sets in Decision-Making 263\u003c\/p\u003e \u003cp\u003e9.5 Comparison of m-Polar Fuzzy Set and Ordinary Fuzzy Sets in Decision-Making 265\u003c\/p\u003e \u003cp\u003e9.6 Analysis of m-Polar FSs 265\u003c\/p\u003e \u003cp\u003e9.6.1 Analysis Based on m-Polar FS Publications 265\u003c\/p\u003e \u003cp\u003e9.6.2 Analysis Based on Journals 267\u003c\/p\u003e \u003cp\u003e9.6.3 Analysis Based on Authors’ Contributions 282\u003c\/p\u003e \u003cp\u003e9.6.4 Analysis Based on Application of m-Polar Fuzzy Logic 284\u003c\/p\u003e \u003cp\u003e9.6.5 Bibliometric Analysis for the m-Polar Fuzzy Set 286\u003c\/p\u003e \u003cp\u003e9.6.5.1 Co-Author and Author Mapping for m-Polar Fuzzy Set 286\u003c\/p\u003e \u003cp\u003e9.6.5.2 Bibliographic Coupling of Universities for the m-Polar Fuzzy Set 287\u003c\/p\u003e \u003cp\u003e9.6.5.3 Bibliographic Coupling Countries for the m-Polar Fuzzy Set 287\u003c\/p\u003e \u003cp\u003e9.6.5.4 Citation Documents Analysis for m-Polar Fuzzy Sets 288\u003c\/p\u003e \u003cp\u003e9.6.5.5 Co-Occurrences of Author’s Keywords Analysis for m-Polar Fuzzy Sets 289\u003c\/p\u003e \u003cp\u003e9.6.5.6 Co-Authorship Organizations Analysis for the m-Polar Fuzzy Sets 290\u003c\/p\u003e \u003cp\u003e9.7 Conclusion 290\u003c\/p\u003e \u003cp\u003eReferences 291\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Bibliometrics Analysis on Renewable Energy and Multi-Criteria Decision-Making 295\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eRahim Arslan\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 296\u003c\/p\u003e \u003cp\u003e10.2 Literature Review 298\u003c\/p\u003e \u003cp\u003e10.3 Methodology 299\u003c\/p\u003e \u003cp\u003e10.3.1 Data Collection 299\u003c\/p\u003e \u003cp\u003e10.3.1.1 Selection of Databases 299\u003c\/p\u003e \u003cp\u003e10.3.1.2 Keyword Search 299\u003c\/p\u003e \u003cp\u003e10.3.1.3 Time Interval 300\u003c\/p\u003e \u003cp\u003e10.3.1.4 Visualization of Data 300\u003c\/p\u003e \u003cp\u003e10.3.2 Data Acquisition 300\u003c\/p\u003e \u003cp\u003e10.4 Bibliometric Indicators 300\u003c\/p\u003e \u003cp\u003e10.4.1 Number of Publications and Citations 301\u003c\/p\u003e \u003cp\u003e10.4.2 Evaluation According to the Amount of Citations 303\u003c\/p\u003e \u003cp\u003e10.4.3 Author and Organization Analysis 303\u003c\/p\u003e \u003cp\u003e10.4.4 Country Analysis 306\u003c\/p\u003e \u003cp\u003e10.4.5 Journal Analysis 308\u003c\/p\u003e \u003cp\u003e10.4.6 Keyword Analysis 309\u003c\/p\u003e \u003cp\u003e10.4.7 Trend Analysis 316\u003c\/p\u003e \u003cp\u003e10.5 Discussion 317\u003c\/p\u003e \u003cp\u003e10.6 Research Gaps and Future Directions 318\u003c\/p\u003e \u003cp\u003eReferences 319\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 4: Bibliometric Analysis in Healthcare and Medicine 323\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Gamification in Healthcare: Bibliometric Analysis on Gamification in Nursing Care 325\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAskeri Çankaya\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 326\u003c\/p\u003e \u003cp\u003e11.1.1 Gamification in Healthcare 326\u003c\/p\u003e \u003cp\u003e11.1.2 Gamification in Nursing Care 327\u003c\/p\u003e \u003cp\u003e11.2 Material and Methods 329\u003c\/p\u003e \u003cp\u003e11.3 Results 330\u003c\/p\u003e \u003cp\u003e11.4 Discussions 334\u003c\/p\u003e \u003cp\u003e11.5 Conclusions 336\u003c\/p\u003e \u003cp\u003eReferences 336\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Virtual Reality in Healthcare: A Bibliometric Analysis of Studies on Wound Care 339\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eHatice Özsoy\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 340\u003c\/p\u003e \u003cp\u003e12.1.1 Virtual Reality in Nursing 340\u003c\/p\u003e \u003cp\u003e12.1.2 Virtual Reality in Wound Care 341\u003c\/p\u003e \u003cp\u003e12.1.3 Literature Review 341\u003c\/p\u003e \u003cp\u003e12.2 Materials and Methods 342\u003c\/p\u003e \u003cp\u003e12.2.1 Research Problem and Aim 342\u003c\/p\u003e \u003cp\u003e12.2.2 Data Sources and Research Methods 343\u003c\/p\u003e \u003cp\u003e12.3 Results 343\u003c\/p\u003e \u003cp\u003e12.3.1 Main Information 343\u003c\/p\u003e \u003cp\u003e12.3.2 Annual Scientific Production 344\u003c\/p\u003e \u003cp\u003e12.3.3 The Most Productive Countries 344\u003c\/p\u003e \u003cp\u003e12.3.4 Author Keywords 345\u003c\/p\u003e \u003cp\u003e12.3.5 Most Productive and Cited Countries 347\u003c\/p\u003e \u003cp\u003e12.3.6 Sankey Diagram 348\u003c\/p\u003e \u003cp\u003e12.3.7 Country Collaboration Network 348\u003c\/p\u003e \u003cp\u003e12.4 Discussion 349\u003c\/p\u003e \u003cp\u003e12.5 Conclusion 350\u003c\/p\u003e \u003cp\u003eReferences 350\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Escape Room Method in Healthcare: A Bibliometric Analysis 355\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eEsra Özkan\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 356\u003c\/p\u003e \u003cp\u003e13.1.1 Escape Rooms in Healthcare 356\u003c\/p\u003e \u003cp\u003e13.1.2 Escape Rooms in Clinical Nursing 357\u003c\/p\u003e \u003cp\u003e13.1.3 The Theory of Escape Room 357\u003c\/p\u003e \u003cp\u003e13.2 Material and Method 358\u003c\/p\u003e \u003cp\u003e13.2.1 Data Extraction and Analysis Process 359\u003c\/p\u003e \u003cp\u003e13.3 Results 360\u003c\/p\u003e \u003cp\u003e13.4 Discussions 363\u003c\/p\u003e \u003cp\u003e13.5 Conclusions 364\u003c\/p\u003e \u003cp\u003eReferences 364\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Bibliometric Analysis of Wavelet Transformation Applications in Biosignal and Medical Image Processing 367\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eS. N. Kumar, Linu Tess Antony and Jibil K. John\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 368\u003c\/p\u003e \u003cp\u003e14.2 Review of the Literature Using Bibliometric Analysis 370\u003c\/p\u003e \u003cp\u003e14.3 Results and Discussion 372\u003c\/p\u003e \u003cp\u003e14.4 Conclusion 386\u003c\/p\u003e \u003cp\u003eReferences 387\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 5: Artificial Intelligence and Machine Learning 389\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Artificial Intelligence in Business Management: Current Developments and Future Perspectives Through Bibliometric Analysis 391\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eZekiye Tamer\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction 392\u003c\/p\u003e \u003cp\u003e15.2 Public Relations in Business Management and AI 393\u003c\/p\u003e \u003cp\u003e15.3 Method 395\u003c\/p\u003e \u003cp\u003e15.3.1 Bibliometric Analysis 395\u003c\/p\u003e \u003cp\u003e15.3.2 Research Gaps and Research Questions 396\u003c\/p\u003e \u003cp\u003e15.3.3 Findings 396\u003c\/p\u003e \u003cp\u003e15.4 Conclusions 409\u003c\/p\u003e \u003cp\u003eReferences 411\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 Decision Trees in Transportation Research: Bibliometric Analysis and Future Directions 413\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eGülay Demir, Prasenjit Chatterjee and Abhijit Saha\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16.1 Introduction 414\u003c\/p\u003e \u003cp\u003e16.2 Literature Review 415\u003c\/p\u003e \u003cp\u003e16.3 Fundamentals of Decision Trees 416\u003c\/p\u003e \u003cp\u003e16.3.1 Types of Decision Trees 417\u003c\/p\u003e \u003cp\u003e16.3.2 Applications of Decision Trees 418\u003c\/p\u003e \u003cp\u003e16.3.3 Basic Components for Decision Trees 419\u003c\/p\u003e \u003cp\u003e16.3.4 Working Principle of Decision Trees 419\u003c\/p\u003e \u003cp\u003e16.3.5 Applications of Decision Trees in Transportation 420\u003c\/p\u003e \u003cp\u003e16.3.6 Decision Tree Model Drawing 420\u003c\/p\u003e \u003cp\u003e16.4 Research Methodology 421\u003c\/p\u003e \u003cp\u003e16.4.1 Data Collection 422\u003c\/p\u003e \u003cp\u003e16.4.2 Bibliometric Analysis Tools 422\u003c\/p\u003e \u003cp\u003e16.4.3 Data Analysis 422\u003c\/p\u003e \u003cp\u003e16.4.4 Bibliometric Indicators 423\u003c\/p\u003e \u003cp\u003e16.4.4.1 Number of Publications and Citations 423\u003c\/p\u003e \u003cp\u003e16.4.5 Number of Citations 425\u003c\/p\u003e \u003cp\u003e16.4.6 Author and Organization Analysis 426\u003c\/p\u003e \u003cp\u003e16.4.7 Country Analysis 428\u003c\/p\u003e \u003cp\u003e16.4.8 Journal Analysis 429\u003c\/p\u003e \u003cp\u003e16.4.9 Keyword Analysis 431\u003c\/p\u003e \u003cp\u003e16.4.10 Trend Analysis 437\u003c\/p\u003e \u003cp\u003e16.5 Discussion 439\u003c\/p\u003e \u003cp\u003e16.6 Conclusions and Future Research Directions 441\u003c\/p\u003e \u003cp\u003eReferences 441\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 Machine Learning in Climate Change from 2015 to 2024: A Bibliometric Analysis 447\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMinh Thu Nguyen\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e17.1 Introduction 447\u003c\/p\u003e \u003cp\u003e17.2 Research Methodology 449\u003c\/p\u003e \u003cp\u003e17.3 Trend of Scientific Articles 450\u003c\/p\u003e \u003cp\u003e17.3.1 Research Productivity in 2015–2024 Year 450\u003c\/p\u003e \u003cp\u003e17.3.2 Publication of Scientific Journals 451\u003c\/p\u003e \u003cp\u003e17.3.3 Output of Author 453\u003c\/p\u003e \u003cp\u003e17.3.4 Distribution of Country 455\u003c\/p\u003e \u003cp\u003e17.4 Conclusions 459\u003c\/p\u003e \u003cp\u003eReferences 460\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 Neuro-Fuzzy Systems and Inference in the Evolution of Intelligent Systems: A Bibliometric Review 463\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eSefer Darıcı\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e18.1 Introduction 464\u003c\/p\u003e \u003cp\u003e18.2 Literature 465\u003c\/p\u003e \u003cp\u003e18.3 Materials and Methods 466\u003c\/p\u003e \u003cp\u003e18.4 Bibliometric Analysis Results of Neuro-Fuzzy Systems and Inference 467\u003c\/p\u003e \u003cp\u003e18.4.1 Performance Analysis 467\u003c\/p\u003e \u003cp\u003e18.4.1.1 Database Overview 467\u003c\/p\u003e \u003cp\u003e18.4.1.2 Annual Publication and Citation Status 468\u003c\/p\u003e \u003cp\u003e18.4.1.3 Publication and Citation Status of Journals 469\u003c\/p\u003e \u003cp\u003e18.4.1.4 The Most Relevant Affiliations 471\u003c\/p\u003e \u003cp\u003e18.4.1.5 Status of Authors 471\u003c\/p\u003e \u003cp\u003e18.4.1.6 The Most Productive Countries 472\u003c\/p\u003e \u003cp\u003e18.4.1.7 Most Cited Document 474\u003c\/p\u003e \u003cp\u003e18.4.2 Scientific Mapping Analysis 475\u003c\/p\u003e \u003cp\u003e18.4.2.1 Thematic Map 475\u003c\/p\u003e \u003cp\u003e18.4.2.2 Trend Topics 476\u003c\/p\u003e \u003cp\u003e18.4.2.3 Keyword Analysis 477\u003c\/p\u003e \u003cp\u003e18.5 Discussion 479\u003c\/p\u003e \u003cp\u003e18.6 Conclusions 482\u003c\/p\u003e \u003cp\u003eReferences 482\u003c\/p\u003e \u003cp\u003e\u003cb\u003e19 Genetic Algorithms in Bioinformatics: A Bibliometric Review 487\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAhmet Turan Demir\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e19.1 Introduction 488\u003c\/p\u003e \u003cp\u003e19.2 Method 490\u003c\/p\u003e \u003cp\u003e19.2.1 Data Collection 490\u003c\/p\u003e \u003cp\u003e19.2.2 Data Analysis 490\u003c\/p\u003e \u003cp\u003e19.2.3 Software Tools 491\u003c\/p\u003e \u003cp\u003e19.3 Results 491\u003c\/p\u003e \u003cp\u003e19.3.1 General Information of Publications 491\u003c\/p\u003e \u003cp\u003e19.3.2 Distribution of Publication and Citation Counts by Year 492\u003c\/p\u003e \u003cp\u003e19.3.3 Most Cited Articles, Countries, and Journals 494\u003c\/p\u003e \u003cp\u003e19.3.4 Most Productive Authors, Institutions, Journals, and Countries 496\u003c\/p\u003e \u003cp\u003e19.3.5 Collaborative Networks and Collaboration Analyses 499\u003c\/p\u003e \u003cp\u003e19.3.6 Thematic Analysis of Popular Research Topics 501\u003c\/p\u003e \u003cp\u003e19.3.7 Trend Topics 503\u003c\/p\u003e \u003cp\u003e19.4 Discussions 506\u003c\/p\u003e \u003cp\u003e19.5 Future Directions and Implications 507\u003c\/p\u003e \u003cp\u003e19.6 Conclusions 508\u003c\/p\u003e \u003cp\u003eReferences 509\u003c\/p\u003e \u003cp\u003e\u003cb\u003e20 Swarm Intelligence in Two Decades: Bibliometric Analysis and Research Visualizations 513\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAyşe Meriç Yazıcı\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e20.1 Introduction 513\u003c\/p\u003e \u003cp\u003e20.2 Bibliometric Analysis 515\u003c\/p\u003e \u003cp\u003e20.3 Methodology 515\u003c\/p\u003e \u003cp\u003e20.4 Data Analysis and Findings 515\u003c\/p\u003e \u003cp\u003e20.5 Theoretical and Practical Limitations 522\u003c\/p\u003e \u003cp\u003e20.6 Future Recommendations 523\u003c\/p\u003e \u003cp\u003e20.7 Conclusions 523\u003c\/p\u003e \u003cp\u003eReferences 524\u003c\/p\u003e \u003cp\u003e\u003cb\u003e21 Bayesian Methods in Marketing: A Bibliometric Examination of Trends and Patterns 527\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eBibin Xavier\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e21.1 Introduction 527\u003c\/p\u003e \u003cp\u003e21.2 Methodology 529\u003c\/p\u003e \u003cp\u003e21.3 Bibliometric Analysis 530\u003c\/p\u003e \u003cp\u003e21.3.1 Annual Scientific Production 530\u003c\/p\u003e \u003cp\u003e21.3.2 Average Citations Per Year 533\u003c\/p\u003e \u003cp\u003e21.3.3 Most Relevant Sources 533\u003c\/p\u003e \u003cp\u003e21.3.4 Most Local Cited Sources 533\u003c\/p\u003e \u003cp\u003e21.3.5 Core Sources by Bradford’s Law 535\u003c\/p\u003e \u003cp\u003e21.3.6 Sources’ Local Impact 539\u003c\/p\u003e \u003cp\u003e21.3.7 Most Relevant Authors 541\u003c\/p\u003e \u003cp\u003e21.3.8 Most Relevant Affiliations 541\u003c\/p\u003e \u003cp\u003e21.3.9 Countries’ Scientific Production 542\u003c\/p\u003e \u003cp\u003e21.3.10 Most Global Cited Documents 543\u003c\/p\u003e \u003cp\u003e21.3.11 Bibliographic Coupling 545\u003c\/p\u003e \u003cp\u003e21.4 Discussion 545\u003c\/p\u003e \u003cp\u003e21.5 Conclusions 548\u003c\/p\u003e \u003cp\u003eReferences 548\u003c\/p\u003e \u003cp\u003e\u003cb\u003e22 Bibliometric Analysis of Search Engine Optimization–Based Decision-Making Strategies 551\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eUzma Mumtaz, Anand Bharathi S., S. Rajamohan and Naseeb Ahmad\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e22.1 Introduction 552\u003c\/p\u003e \u003cp\u003e22.1.1 Fundamentals of Search Engine Optimization (seo) 552\u003c\/p\u003e \u003cp\u003e22.1.2 Introduction to Bibliometric Analysis in SEO Decision-Making 552\u003c\/p\u003e \u003cp\u003e22.1.3 Objectives and Scope of the Chapter 553\u003c\/p\u003e \u003cp\u003e22.1.4 Selection Criteria for Scopus Search 554\u003c\/p\u003e \u003cp\u003e22.2 Insights through Research Publication Trends 554\u003c\/p\u003e \u003cp\u003e22.2.1 Analysis of Annual Publication Trends in Informed SEO Decision-Making Strategies 554\u003c\/p\u003e \u003cp\u003e22.2.2 Key Milestones and Landmark Publications 556\u003c\/p\u003e \u003cp\u003e22.2.3 Trends in Publication Activity Over Time 556\u003c\/p\u003e \u003cp\u003e22.2.4 Impact of External Factors on Publication Trends 557\u003c\/p\u003e \u003cp\u003e22.3 Prominent Authors, Organizations, and Countries 557\u003c\/p\u003e \u003cp\u003e22.3.1 Top Authors and Their Citation Impact 557\u003c\/p\u003e \u003cp\u003e22.3.2 Leading Academic Institutions and Their Contributions 557\u003c\/p\u003e \u003cp\u003e22.3.3 Global Distribution of Research Output and Impact 558\u003c\/p\u003e \u003cp\u003e22.4 Most Influential Journals and Articles 559\u003c\/p\u003e \u003cp\u003e22.4.1 Analysis of Most Influential Journals 559\u003c\/p\u003e \u003cp\u003e22.4.2 Examination of Highly Cited Articles and their Impact 560\u003c\/p\u003e \u003cp\u003e22.4.3 Key Insights from Influential Articles 562\u003c\/p\u003e \u003cp\u003e22.5 Analysis of Co-Citations and Author Co-Citation Networks 562\u003c\/p\u003e \u003cp\u003e22.5.1 Co-Citation Analysis: Identifying Frequently Cited References 562\u003c\/p\u003e \u003cp\u003e22.5.2 Author Co-Citation Networks: Mapping Collaborative Partnerships 564\u003c\/p\u003e \u003cp\u003e22.5.3 Insights from Co-Citation Analysis 565\u003c\/p\u003e \u003cp\u003e22.6 Keyword Co-Occurrence Analysis 566\u003c\/p\u003e \u003cp\u003e22.6.1 Top Keywords in Informed SEO Decision-Making Strategies 566\u003c\/p\u003e \u003cp\u003e22.6.2 Analysis of Keyword Relationships and Frequency 566\u003c\/p\u003e \u003cp\u003e22.6.3 Insights for Research and Practice 568\u003c\/p\u003e \u003cp\u003e22.7 Thematic Analysis of Bibliometric Coupling 569\u003c\/p\u003e \u003cp\u003e22.7.1 Identification of Theme Clusters in Informed SEO-Based Decision-Making Strategies 569\u003c\/p\u003e \u003cp\u003e22.7.2 Overview of Key Research Themes and Findings 573\u003c\/p\u003e \u003cp\u003e22.7.3 Implications for Future Research Directions 573\u003c\/p\u003e \u003cp\u003e22.8 Challenges and Opportunities 574\u003c\/p\u003e \u003cp\u003e22.8.1 Limitations and Pitfalls of Bibliometric Analysis in SEO 574\u003c\/p\u003e \u003cp\u003e22.8.2 Opportunities for Further Research and Innovation 574\u003c\/p\u003e \u003cp\u003e22.8.3 Addressing Challenges in Bibliometric Analysis for Informed SEO Decision-Making 575\u003c\/p\u003e \u003cp\u003e22.9 Conclusions 575\u003c\/p\u003e \u003cp\u003e22.9.1 Recap of Key Findings and Insights 575\u003c\/p\u003e \u003cp\u003e22.9.2 Importance of Bibliometric Analysis in SEO Strategy 576\u003c\/p\u003e \u003cp\u003e22.9.3 Future Outlook and Recommendations for Practitioners Insights through Research 576\u003c\/p\u003e \u003cp\u003eAcknowledgment 576\u003c\/p\u003e \u003cp\u003eReferences 577\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 6: Technology, Sustainability, and Innovation 581\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e23 Bibliometric Insights into the Nexus of Digital HR, Innovation, and Sustainability: Toward a Smart Workforce 583\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eShivakami Rajan and L. R. Niranjan\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e23.1 Introduction 584\u003c\/p\u003e \u003cp\u003e23.1.1 Research Gap 584\u003c\/p\u003e \u003cp\u003e23.1.2 Research Questions 584\u003c\/p\u003e \u003cp\u003e23.1.3 Literature Review 585\u003c\/p\u003e \u003cp\u003e23.1.4 Conceptual Framework 587\u003c\/p\u003e \u003cp\u003e23.2 Methodology 588\u003c\/p\u003e \u003cp\u003e23.2.1 Inclusion and Exclusion Criteria 589\u003c\/p\u003e \u003cp\u003e23.2.2 Data Analysis 589\u003c\/p\u003e \u003cp\u003e23.3 Results-Bibliometric Findings 589\u003c\/p\u003e \u003cp\u003e23.3.1 Descriptive Details of Publications 589\u003c\/p\u003e \u003cp\u003e23.3.2 Keyword Analyses 590\u003c\/p\u003e \u003cp\u003e23.3.3 Authors 593\u003c\/p\u003e \u003cp\u003e23.3.4 Findings 596\u003c\/p\u003e \u003cp\u003e23.4 Discussions 600\u003c\/p\u003e \u003cp\u003e23.5 Implications 603\u003c\/p\u003e \u003cp\u003e23.5.1 Industry 603\u003c\/p\u003e \u003cp\u003e23.5.2 Managerial 603\u003c\/p\u003e \u003cp\u003e23.6 Future Directions 604\u003c\/p\u003e \u003cp\u003e23.7 Conclusions 605\u003c\/p\u003e \u003cp\u003eReferences 605\u003c\/p\u003e \u003cp\u003e\u003cb\u003e24 Delineation of Blockchain and Customer Experience: A Review and Thematic Analysis 615\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAkshay Kumar Mishra and Sandeep Kumar Mohanty\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e24.1 Introduction 615\u003c\/p\u003e \u003cp\u003e24.2 Conceptual Background: Blockchain and Customer Experience 617\u003c\/p\u003e \u003cp\u003e24.3 Methodology 618\u003c\/p\u003e \u003cp\u003e24.4 Bibliometric and Network Analysis 619\u003c\/p\u003e \u003cp\u003e24.4.1 Performance Analysis 619\u003c\/p\u003e \u003cp\u003e24.4.2 Influential Documents Analysis 621\u003c\/p\u003e \u003cp\u003e24.4.3 Keywords and Network Analysis 623\u003c\/p\u003e \u003cp\u003e24.4.4 Thematic Analysis 625\u003c\/p\u003e \u003cp\u003e24.4.4.1 Blockchain, Artificial Intelligence, and Customer Experience 626\u003c\/p\u003e \u003cp\u003e24.4.4.2 Blockchain and Competition 627\u003c\/p\u003e \u003cp\u003e24.4.4.3 Blockchain and Motivation 628\u003c\/p\u003e \u003cp\u003e24.4.4.4 Blockchain and Cost Reduction 628\u003c\/p\u003e \u003cp\u003e24.5 Implications and Future Research Directions 629\u003c\/p\u003e \u003cp\u003e24.6 Conclusion 632\u003c\/p\u003e \u003cp\u003eReferences 633\u003c\/p\u003e \u003cp\u003e\u003cb\u003e25 A Post-Millennial Bibliometric Analysis of Algorithmic Fairness: Trends, Research Barriers, and Future Directions 639\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMurat Atan, Mustafa Mehmet Bayar and Irmak Uzun Bayar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e25.1 Introduction 640\u003c\/p\u003e \u003cp\u003e25.1.1 Explainable AI and the Fairness Hype from a Data-Driven Decision-Making Perspective 640\u003c\/p\u003e \u003cp\u003e25.1.2 Why Focus on the Post-Millennial Era? 641\u003c\/p\u003e \u003cp\u003e25.2 Relevant Bibliometric Analyses 641\u003c\/p\u003e \u003cp\u003e25.3 Materials and Methods 643\u003c\/p\u003e \u003cp\u003e25.4 Bibliometric and Network Analysis 645\u003c\/p\u003e \u003cp\u003e25.4.1 Sources 645\u003c\/p\u003e \u003cp\u003e25.4.2 Annual Monitoring of Growth 648\u003c\/p\u003e \u003cp\u003e25.4.3 Language Choices 650\u003c\/p\u003e \u003cp\u003e25.4.4 Subject Areas 650\u003c\/p\u003e \u003cp\u003e25.4.5 Keyword Analysis 653\u003c\/p\u003e \u003cp\u003e25.4.6 Geographical Distribution of Publications and International Collaborations 656\u003c\/p\u003e \u003cp\u003e25.4.7 Authorship 657\u003c\/p\u003e \u003cp\u003e25.4.8 Institutional Performance 664\u003c\/p\u003e \u003cp\u003e25.4.9 Research Barriers and Funding Impact 666\u003c\/p\u003e \u003cp\u003e25.5 Conclusion 666\u003c\/p\u003e \u003cp\u003eReferences 668\u003c\/p\u003e \u003cp\u003eIndex 673\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Computer science [\u003ca title=\"See our other books on Computer science\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Computer%20science%20%5BUY%5D%22\"\u003eUY\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley-Scrivener","offers":[{"title":"Brand New","offer_id":52433517052184,"sku":"9781394302529","price":214.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781394302529.jpg?v=1784853426","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/bibliometric-analyses-in-data-driven-decision-making-hardback-9781394302529","provider":"Freshly Printed Books","version":"1.0","type":"link"}