World's Best Scientists 2026 revealed!
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Business and Management
China
2026

D-Index & Metrics

Business and Management

D-Index
85
Citations
33742
World Ranking
124
National Ranking
9

Computer Science

D-Index
82
Citations
32916
World Ranking
945
National Ranking
139

Eric W.T. Ngai publication distribution in Business and Management in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Business and Management in 2026. The highlighted bar marks where Eric W.T. Ngai sits on this spectrum.

35–39 publications: 2 scientists 40–44 publications: 2 scientists 45–49 publications: 5 scientists 50–54 publications: 20 scientists 55–59 publications: 39 scientists 60–64 publications: 66 scientists 65–69 publications: 52 scientists 70–74 publications: 80 scientists 75–79 publications: 83 scientists 80–84 publications: 116 scientists 85–89 publications: 94 scientists 90–94 publications: 111 scientists 95–99 publications: 122 scientists 100–104 publications: 104 scientists 105–109 publications: 113 scientists 110–114 publications: 96 scientists 115–119 publications: 97 scientists 120–124 publications: 112 scientists 125–129 publications: 93 scientists 130–134 publications: 79 scientists 135–139 publications: 69 scientists 140–144 publications: 80 scientists 145–149 publications: 81 scientists 150–154 publications: 85 scientists 155–159 publications: 50 scientists 160–164 publications: 74 scientists 165–169 publications: 61 scientists 170–174 publications: 40 scientists 175–179 publications: 44 scientists 180–184 publications: 47 scientists 185–189 publications: 59 scientists 190–194 publications: 35 scientists 195–199 publications: 37 scientists 200–204 publications: 49 scientists 205–209 publications: 48 scientists 210–214 publications: 34 scientists 215–219 publications: 31 scientists 220–224 publications: 37 scientists 225–229 publications: 34 scientists 230–234 publications: 25 scientists 235–239 publications: 28 scientists 240–244 publications: 34 scientists 245–249 publications: 28 scientists 250–254 publications: 23 scientists 255–259 publications: 22 scientists 260–264 publications: 11 scientists 265–269 publications: 16 scientists 270–274 publications: 23 scientists 275–279 publications: 12 scientists 280–284 publications: 16 scientists 285–289 publications: 10 scientists 290–294 publications: 12 scientists 295–299 publications: 12 scientists 300–304 publications: 8 scientists 305–309 publications: 13 scientists 310–314 publications: 13 scientists 315–319 publications: 6 scientists 320–324 publications: 10 scientists 325–329 publications: 9 scientists 330–334 publications: 7 scientists 335–339 publications: 10 scientists 340–344 publications: 10 scientists 345–349 publications: 7 scientists 350–354 publications: 4 scientists 355–359 publications: 10 scientists 360–364 publications: 3 scientists 365–369 publications: 7 scientists 370–374 publications: 2 scientists 375–379 publications: 8 scientists 380–384 publications: 4 scientists 385–389 publications: 5 scientists 390–394 publications: 5 scientists 395–399 publications: 2 scientists 400–404 publications: 2 scientists 405–409 publications: 4 scientists 410–414 publications: 3 scientists 415–419 publications: 2 scientists 420–424 publications: 5 scientists 425–429 publications: 3 scientists 430–434 publications: 1 scientists 435 publications: 1 scientists 436+ publications: 100 scientists
35 publications 436+

This scientist: 244 publications — 85th percentile

85% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 436 publications or more.

Eric W.T. Ngai D-index placement in Business and Management in 2026

The chart shows the D-index (discipline H-index) distribution of Business and Management scientists ranked by Research.com in 2026. The highlighted bar marks where Eric W.T. Ngai sits on this spectrum.

30 D-Index: 156 scientists 31 D-Index: 159 scientists 32 D-Index: 171 scientists 33 D-Index: 161 scientists 34 D-Index: 135 scientists 35 D-Index: 124 scientists 36 D-Index: 114 scientists 37 D-Index: 111 scientists 38 D-Index: 103 scientists 39 D-Index: 89 scientists 40 D-Index: 81 scientists 41 D-Index: 97 scientists 42 D-Index: 80 scientists 43 D-Index: 69 scientists 44 D-Index: 68 scientists 45 D-Index: 63 scientists 46 D-Index: 54 scientists 47 D-Index: 69 scientists 48 D-Index: 50 scientists 49 D-Index: 58 scientists 50 D-Index: 54 scientists 51 D-Index: 62 scientists 52 D-Index: 54 scientists 53 D-Index: 43 scientists 54 D-Index: 49 scientists 55 D-Index: 35 scientists 56 D-Index: 40 scientists 57 D-Index: 44 scientists 58 D-Index: 34 scientists 59 D-Index: 29 scientists 60 D-Index: 48 scientists 61 D-Index: 32 scientists 62 D-Index: 30 scientists 63 D-Index: 22 scientists 64 D-Index: 22 scientists 65 D-Index: 19 scientists 66 D-Index: 20 scientists 67 D-Index: 18 scientists 68 D-Index: 17 scientists 69 D-Index: 21 scientists 70 D-Index: 20 scientists 71 D-Index: 19 scientists 72 D-Index: 14 scientists 73 D-Index: 10 scientists 74 D-Index: 16 scientists 75 D-Index: 24 scientists 76 D-Index: 13 scientists 77 D-Index: 19 scientists 78 D-Index: 8 scientists 79 D-Index: 6 scientists 80 D-Index: 4 scientists 81 D-Index: 12 scientists 82 D-Index: 7 scientists 83 D-Index: 7 scientists 84 D-Index: 6 scientists 85 D-Index: 10 scientists 86 D-Index: 4 scientists 87 D-Index: 11 scientists 88 D-Index: 6 scientists 89+ D-Index: 96 scientists
30 D-Index 89+

This scientist: 85 D-Index — 96th percentile

96% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 89 D-Index or more.

Research.com Recognitions

  • 2026 - Research.com Business and Management in China Leader Award
  • 2025 - Research.com Business and Management in China Leader Award
  • 2024 - Research.com Business and Management in China Leader Award
  • 2023 - Research.com Business and Management in China Leader Award

Overview

Eric W.T. Ngai is affiliated with the Hong Kong Polytechnic University in China. Their research primarily focuses on the field of Business, Management and Accounting, with 57 publications in this area. Within this, their work spans various subfields, including Strategy and Management, Sociology and Political Science, Management Information Systems, Information Systems, and Management Science and Operations Research.

The scientist has contributed to several main research topics, encompassing Digital Marketing and Social Media, Supply Chain Resilience and Risk Management, Technology Adoption and User Behaviour, Big Data and Business Intelligence, Blockchain Technology Applications and Security, Sustainable Supply Chain Management, and Competitive and Knowledge Intelligence.

Eric W.T. Ngai has frequently published in notable venues such as:

  • Annals of Operations Research
  • Internet Research
  • SSRN Electronic Journal
  • Information & Management
  • Journal of Business Research

Their recent papers include:

  • "Deep learning in computer vision: A critical review of emerging techniques and application scenarios" (2021) published in Machine Learning with Applications
  • "A note on big data analytics capability development in supply chain" (2020) published in Decision Support Systems
  • "The implementation of artificial intelligence in organizations: A systematic literature review" (2023) published in Information & Management
  • "Machine learning in marketing: A literature review, conceptual framework, and research agenda" (2022) published in Journal of Business Research
  • "Impact of artificial intelligence investment on firm value" (2021) published in Annals of Operations Research

Eric W.T. Ngai has collaborated extensively with several coauthors, including Ariel K.H. Lui, David T.W. Wong, Ashish Kumar Jha, Maggie C. M. Lee, and Ajay Kumar.

Best Publications

  • Review: Application of data mining techniques in customer relationship management: A literature review and classification

    E. W. T. Ngai;Li Xiu;D. C. K. Chau

  • Information systems in supply chain integration and management

    Angappa Gunasekaran;Eric W. T. Ngai

  • The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature

    E. W. T. Ngai;Yong Hu;Y. H. Wong;Yijun Chen

  • Big data analytics in logistics and supply chain management: Certain investigations for research and applications

    Gang Wang;Angappa Gunasekaran;Eric W.T. Ngai;Thanos Papadopoulos

  • Application of decision-making techniques in supplier selection: A systematic review of literature

    Junyi Chai;James N. K. Liu;Eric W. T. Ngai

  • Empirical examination of the adoption of WebCT using TAM

    Eric W. T. Ngai;J. K. L. Poon;Y. H. C. Chan

  • RFID research: An academic literature review (1995–2005) and future research directions

    E.W.T. Ngai;Karen K.L. Moon;Frederick J. Riggins;Candace Y. Yi

  • Examining the critical success factors in the adoption of enterprise resource planning

    E. W. T. Ngai;C. C. H. Law;F. K. T. Wat

  • A review for mobile commerce research and applications

    E. W. T. Ngai;A. Gunasekaran

  • Social media research

    Eric W.T. Ngai;Spencer S.C. Tao;Karen K.L. Moon

  • Build-to-order supply chain management: a literature review and framework for development

    A. Gunasekaran;E.W.T. Ngai

  • A literature review and classification of electronic commerce research

    E. W. T. Ngai;F. K. T. Wat

  • Deep learning in computer vision: A critical review of emerging techniques and application scenarios

    Junyi Chai;Junyi Chai;Hao Zeng;Anming Li;Eric W.T. Ngai

  • Customer relationship management research (1992‐2002): An academic literature review and classification

    E.W.T. Ngai

  • Measures for evaluating supply chain performance in transport logistics

    Kee-hung Lai;E.W.T Ngai;T.C.E Cheng

  • Extending the understanding of end user information systems satisfaction formation: an equitable needs fulfillment model approach

    N. Au;E. W. T. Ngai;T. C. E. Cheng

  • ERP systems adoption: An exploratory study of the organizational factors and impacts of ERP success

    Chuck C. H. Law;Eric W. T. Ngai

  • Customer churn prediction using improved balanced random forests

    Yaya Xie;Xiu Li;E. W. T. Ngai;Weiyun Ying

  • Information technology, operational, and management competencies for supply chain agility: Findings from case studies

    Eric W. T. Ngai;Dorothy C. K. Chau;T. L. A. Chan

  • Conceptualising electronic word of mouth activity: An input‐process‐output perspective

    Yolanda Y.Y. Chan;E.W.T. Ngai

Frequent Co-Authors

Angappa Gunasekaran
Angappa Gunasekaran Penn State Harrisburg
T.C.E. Cheng
T.C.E. Cheng Hong Kong Polytechnic University
Samuel Fosso Wamba
Samuel Fosso Wamba Toulouse Business School
Kee-hung Lai
Kee-hung Lai Hong Kong Polytechnic University
Alain Yee-Loong Chong
Alain Yee-Loong Chong University of Nottingham
Shahriar Akter
Shahriar Akter University of Wollongong
Nenad Mladenović
Nenad Mladenović Khalifa University
Pierre Hansen
Pierre Hansen HEC Montréal
Rameshwar Dubey
Rameshwar Dubey Montpellier Business School
Vincent C. S. Heung
Vincent C. S. Heung Hong Kong Polytechnic University

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