Chatterjee / Saha / Kadry | Bibliometric Analyses in Data-Driven Decision-Making | Buch | 978-1-394-30252-9 | sack.de

Buch, Englisch, 720 Seiten

Chatterjee / Saha / Kadry

Bibliometric Analyses in Data-Driven Decision-Making


1. Auflage 2025
ISBN: 978-1-394-30252-9
Verlag: Wiley

Buch, Englisch, 720 Seiten

ISBN: 978-1-394-30252-9
Verlag: Wiley


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.

Chatterjee / Saha / Kadry Bibliometric Analyses in Data-Driven Decision-Making jetzt bestellen!

Weitere Infos & Material


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 Keles 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 Aydin

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

References 291

10 Bibliometrics Analysis on Renewable Energy and Multi-Criteria Decision-Making 295
Rahim Arslan

10.1 Introduction 296

10.2 Literature Review 298

10.3 Methodology 299

10.3.1 Data Collection 299

10.3.1.1 Selection of Databases 299

10.3.1.2 Keyword Search 299

10.3.1.3 Time Interval 300

10.3.1.4 Visualization of Data 300

10.3.2 Data Acquisition 300

10.4 Bibliometric Indicators 300

10.4.1 Number of Publications and Citations 301

10.4.2 Evaluation According to the Amount of Citations 303

10.4.3 Author and Organization Analysis 303

10.4.4 Country Analysis 306

10.4.5 Journal Analysis 308

10.4.6 Keyword Analysis 309

10.4.7 Trend Analysis 316

10.5 Discussion 317

10.6 Research Gaps and Future Directions 318

References 319

Part 4: Bibliometric Analysis in Healthcare and Medicine 323

11 Gamification in Healthcare: Bibliometric Analysis on Gamification in Nursing Care 325
Askeri Çankaya

11.1 Introduction 326

11.1.1 Gamification in Healthcare 326

11.1.2 Gamification in Nursing Care 327

11.2 Material and Methods 329

11.3 Results 330

11.4 Discussions 334

11.5 Conclusions 336

References 336

12 Virtual Reality in Healthcare: A Bibliometric Analysis of Studies on Wound Care 339
Hatice Özsoy

12.1 Introduction 340

12.1.1 Virtual Reality in Nursing 340

12.1.2 Virtual Reality in Wound Care 341

12.1.3 Literature Review 341

12.2 Materials and Methods 342

12.2.1 Research Problem and Aim 342

12.2.2 Data Sources and Research Methods 343

12.3 Results 343

12.3.1 Main Information 343

12.3.2 Annual Scientific Production 344

12.3.3 The Most Productive Countries 344

12.3.4 Author Keywords 345

12.3.5 Most Productive and Cited Countries 347

12.3.6 Sankey Diagram 348

12.3.7 Country Collaboration Network 348

12.4 Discussion 349

12.5 Conclusion 350

References 350

13 Escape Room Method in Healthcare: A Bibliometric Analysis 355
Esra Özkan

13.1 Introduction 356

13.1.1 Escape Rooms in Healthcare 356

13.1.2 Escape Rooms in Clinical Nursing 357

13.1.3 The Theory of Escape Room 357

13.2 Material and Method 358

13.2.1 Data Extraction and Analysis Process 359

13.3 Results 360

13.4 Discussions 363

13.5 Conclusions 364

References 364

14 Bibliometric Analysis of Wavelet Transformation Applications in Biosignal and Medical Image Processing 367
S. N. Kumar, Linu Tess Antony and Jibil K. John

14.1 Introduction 368

14.2 Review of the Literature Using Bibliometric Analysis 370

14.3 Results and Discussion 372

14.4 Conclusion 386

References 387

Part 5: Artificial Intelligence and Machine Learning 389

15 Artificial Intelligence in Business Management: Current Developments and Future Perspectives Through Bibliometric Analysis 391
Zekiye Tamer

15.1 Introduction 392

15.2 Public Relations in Business Management and AI 393

15.3 Method 395

15.3.1 Bibliometric Analysis 395

15.3.2 Research Gaps and Research Questions 396

15.3.3 Findings 396

15.4 Conclusions 409

References 411

16 Decision Trees in Transportation Research: Bibliometric Analysis and Future Directions 413
Gülay Demir, Prasenjit Chatterjee and Abhijit Saha

16.1 Introduction 414

16.2 Literature Review 415

16.3 Fundamentals of Decision Trees 416

16.3.1 Types of Decision Trees 417

16.3.2 Applications of Decision Trees 418

16.3.3 Basic Components for Decision Trees 419

16.3.4 Working Principle of Decision Trees 419

16.3.5 Applications of Decision Trees in Transportation 420

16.3.6 Decision Tree Model Drawing 420

16.4 Research Methodology 421

16.4.1 Data Collection 422

16.4.2 Bibliometric Analysis Tools 422

16.4.3 Data Analysis 422

16.4.4 Bibliometric Indicators 423

16.4.4.1 Number of Publications and Citations 423

16.4.5 Number of Citations 425

16.4.6 Author and Organization Analysis 426

16.4.7 Country Analysis 428

16.4.8 Journal Analysis 429

16.4.9 Keyword Analysis 431

16.4.10 Trend Analysis 437

16.5 Discussion 439

16.6 Conclusions and Future Research Directions 441

References 441

17 Machine Learning in Climate Change from 2015 to 2024: A Bibliometric Analysis 447
Minh Thu Nguyen

17.1 Introduction 447

17.2 Research Methodology 449

17.3 Trend of Scientific Articles 450

17.3.1 Research Productivity in 2015–2024 Year 450

17.3.2 Publication of Scientific Journals 451

17.3.3 Output of Author 453

17.3.4 Distribution of Country 455

17.4 Conclusions 459

References 460

18 Neuro-Fuzzy Systems and Inference in the Evolution of Intelligent Systems: A Bibliometric Review 463
Sefer Darici

18.1 Introduction 464

18.2 Literature 465

18.3 Materials and Methods 466

18.4 Bibliometric Analysis Results of Neuro-Fuzzy Systems and Inference 467

18.4.1 Performance Analysis 467

18.4.1.1 Database Overview 467

18.4.1.2 Annual Publication and Citation Status 468

18.4.1.3 Publication and Citation Status of Journals 469

18.4.1.4 The Most Relevant Affiliations 471

18.4.1.5 Status of Authors 471

18.4.1.6 The Most Productive Countries 472

18.4.1.7 Most Cited Document 474

18.4.2 Scientific Mapping Analysis 475

18.4.2.1 Thematic Map 475

18.4.2.2 Trend Topics 476

18.4.2.3 Keyword Analysis 477

18.5 Discussion 479

18.6 Conclusions 482

References 482

19 Genetic Algorithms in Bioinformatics: A Bibliometric Review 487
Ahmet Turan Demir

19.1 Introduction 488

19.2 Method 490

19.2.1 Data Collection 490

19.2.2 Data Analysis 490

19.2.3 Software Tools 491

19.3 Results 491

19.3.1 General Information of Publications 491

19.3.2 Distribution of Publication and Citation Counts by Year 492

19.3.3 Most Cited Articles, Countries, and Journals 494

19.3.4 Most Productive Authors, Institutions, Journals, and Countries 496

19.3.5 Collaborative Networks and Collaboration Analyses 499

19.3.6 Thematic Analysis of Popular Research Topics 501

19.3.7 Trend Topics 503

19.4 Discussions 506

19.5 Future Directions and Implications 507

19.6 Conclusions 508

References 509

20 Swarm Intelligence in Two Decades: Bibliometric Analysis and Research Visualizations 513
Ayse Meriç Yazici

20.1 Introduction 513

20.2 Bibliometric Analysis 515

20.3 Methodology 515

20.4 Data Analysis and Findings 515

20.5 Theoretical and Practical Limitations 522

20.6 Future Recommendations 523

20.7 Conclusions 523

References 524

21 Bayesian Methods in Marketing: A Bibliometric Examination of Trends and Patterns 527
Bibin Xavier

21.1 Introduction 527

21.2 Methodology 529

21.3 Bibliometric Analysis 530

21.3.1 Annual Scientific Production 530

21.3.2 Average Citations Per Year 533

21.3.3 Most Relevant Sources 533

21.3.4 Most Local Cited Sources 533

21.3.5 Core Sources by Bradford’s Law 535

21.3.6 Sources’ Local Impact 539

21.3.7 Most Relevant Authors 541

21.3.8 Most Relevant Affiliations 541

21.3.9 Countries’ Scientific Production 542

21.3.10 Most Global Cited Documents 543

21.3.11 Bibliographic Coupling 545

21.4 Discussion 545

21.5 Conclusions 548

References 548

22 Bibliometric Analysis of Search Engine Optimization–Based Decision-Making Strategies 551
Uzma Mumtaz, Anand Bharathi S., S. Rajamohan and Naseeb Ahmad

22.1 Introduction 552

22.1.1 Fundamentals of Search Engine Optimization (seo) 552

22.1.2 Introduction to Bibliometric Analysis in SEO Decision-Making 552

22.1.3 Objectives and Scope of the Chapter 553

22.1.4 Selection Criteria for Scopus Search 554

22.2 Insights through Research Publication Trends 554

22.2.1 Analysis of Annual Publication Trends in Informed SEO Decision-Making Strategies 554

22.2.2 Key Milestones and Landmark Publications 556

22.2.3 Trends in Publication Activity Over Time 556

22.2.4 Impact of External Factors on Publication Trends 557

22.3 Prominent Authors, Organizations, and Countries 557

22.3.1 Top Authors and Their Citation Impact 557

22.3.2 Leading Academic Institutions and Their Contributions 557

22.3.3 Global Distribution of Research Output and Impact 558

22.4 Most Influential Journals and Articles 559

22.4.1 Analysis of Most Influential Journals 559

22.4.2 Examination of Highly Cited Articles and their Impact 560

22.4.3 Key Insights from Influential Articles 562

22.5 Analysis of Co-Citations and Author Co-Citation Networks 562

22.5.1 Co-Citation Analysis: Identifying Frequently Cited References 562

22.5.2 Author Co-Citation Networks: Mapping Collaborative Partnerships 564

22.5.3 Insights from Co-Citation Analysis 565

22.6 Keyword Co-Occurrence Analysis 566

22.6.1 Top Keywords in Informed SEO Decision-Making Strategies 566

22.6.2 Analysis of Keyword Relationships and Frequency 566

22.6.3 Insights for Research and Practice 568

22.7 Thematic Analysis of Bibliometric Coupling 569

22.7.1 Identification of Theme Clusters in Informed SEO-Based Decision-Making Strategies 569

22.7.2 Overview of Key Research Themes and Findings 573

22.7.3 Implications for Future Research Directions 573

22.8 Challenges and Opportunities 574

22.8.1 Limitations and Pitfalls of Bibliometric Analysis in SEO 574

22.8.2 Opportunities for Further Research and Innovation 574

22.8.3 Addressing Challenges in Bibliometric Analysis for Informed SEO Decision-Making 575

22.9 Conclusions 575

22.9.1 Recap of Key Findings and Insights 575

22.9.2 Importance of Bibliometric Analysis in SEO Strategy 576

22.9.3 Future Outlook and Recommendations for Practitioners Insights through Research 576

Acknowledgment 576

References 577

Part 6: Technology, Sustainability, and Innovation 581

23 Bibliometric Insights into the Nexus of Digital HR, Innovation, and Sustainability: Toward a Smart Workforce 583
Shivakami Rajan and L. R. Niranjan

23.1 Introduction 584

23.1.1 Research Gap 584

23.1.2 Research Questions 584

23.1.3 Literature Review 585

23.1.4 Conceptual Framework 587

23.2 Methodology 588

23.2.1 Inclusion and Exclusion Criteria 589

23.2.2 Data Analysis 589

23.3 Results-Bibliometric Findings 589

23.3.1 Descriptive Details of Publications 589

23.3.2 Keyword Analyses 590

23.3.3 Authors 593

23.3.4 Findings 596

23.4 Discussions 600

23.5 Implications 603

23.5.1 Industry 603

23.5.2 Managerial 603

23.6 Future Directions 604

23.7 Conclusions 605

References 605

24 Delineation of Blockchain and Customer Experience: A Review and Thematic Analysis 615
Akshay Kumar Mishra and Sandeep Kumar Mohanty

24.1 Introduction 615

24.2 Conceptual Background: Blockchain and Customer Experience 617

24.3 Methodology 618

24.4 Bibliometric and Network Analysis 619

24.4.1 Performance Analysis 619

24.4.2 Influential Documents Analysis 621

24.4.3 Keywords and Network Analysis 623

24.4.4 Thematic Analysis 625

24.4.4.1 Blockchain, Artificial Intelligence, and Customer Experience 626

24.4.4.2 Blockchain and Competition 627

24.4.4.3 Blockchain and Motivation 628

24.4.4.4 Blockchain and Cost Reduction 628

24.5 Implications and Future Research Directions 629

24.6 Conclusion 632

References 633

25 A Post-Millennial Bibliometric Analysis of Algorithmic Fairness: Trends, Research Barriers, and Future Directions 639
Murat Atan, Mustafa Mehmet Bayar and Irmak Uzun Bayar

25.1 Introduction 640

25.1.1 Explainable AI and the Fairness Hype from a Data-Driven Decision-Making Perspective 640

25.1.2 Why Focus on the Post-Millennial Era? 641

25.2 Relevant Bibliometric Analyses 641

25.3 Materials and Methods 643

25.4 Bibliometric and Network Analysis 645

25.4.1 Sources 645

25.4.2 Annual Monitoring of Growth 648

25.4.3 Language Choices 650

25.4.4 Subject Areas 650

25.4.5 Keyword Analysis 653

25.4.6 Geographical Distribution of Publications and International Collaborations 656

25.4.7 Authorship 657

25.4.8 Institutional Performance 664

25.4.9 Research Barriers and Funding Impact 666

25.5 Conclusion 666

References 668

Index 673


Prasenjit Chatterjee, PhD is a post-doctoral fellow in the Department of Applied Data Science, Noroff University College, and a professor of mechanical engineering and Dean of Research and Consultancy at the MCKV Institute of Engineering, India. He has published over 135 research papers in various international journals and conferences, authored and edited more than 43 books on intelligent decision-making, fuzzy computing, supply chain management, optimization techniques, risk management, and sustainability modelling.

Abhijit Saha, PhD is an assistant professor in the Department of Computing Technologies at SRM Institute of Science and Technology, Tamil Nadu, India with over ten years of teaching and research experience. He has published over 50 research articles in international journals and serves on the editorial boards of three international journals. His research interests encompass fuzzy set theory, soft set theory, aggregation operators, optimization, and decision-making.

Seifedine Kadry, PhD is a professor in the Department of Computer Science and Mathematics at the Lebanese American University and the Department of Applied Data Science at Noroff University College. He has published over 100 peer-reviewed papers and authored several books. His research interests include data science, system prognostics, stochastic systems, smart learning, social network analysis, and e-systems.

Gülay Demir, PhD is affiliated with Sivas Cumhuriyet University Vocational School of Health Services. She has over 75 publications, primarily in graduate-level textbooks. Her research interests include fuzzy logic, multi-criteria analysis, mathematical statistics, statistical analysis, data analysis, non-parametric statistics, statistical calculation, and parametric statistics.



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