World's Best Scientists 2026 revealed!
Award Badge
Rising Stars
2025

D-Index & Metrics

Rising Stars

D-Index
53
Citations
9292
World Ranking
251
National Ranking
7

Engineering and Technology

D-Index
57
Citations
8772
World Ranking
2741
National Ranking
40

Kum Fai Yuen publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Kum Fai Yuen sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 180 publications — 40th percentile

40% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Kum Fai Yuen D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Kum Fai Yuen sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 57 D-Index — 74th percentile

74% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Kum Fai Yuen is affiliated with Nanyang Technological University in Singapore and has a significant body of research spanning business, management, accounting, and engineering. Their work addresses a variety of interdisciplinary topics within these fields, with particular focus on marketing, industrial and manufacturing engineering, and strategy and management.

Their research extensively covers key subjects including:

  • Maritime Ports and Logistics
  • Consumer Retail Behavior Studies
  • Technology Adoption and User Behaviour
  • Sharing Economy and Platforms
  • Sustainable Supply Chain Management
  • Digital Marketing and Social Media
  • Maritime Navigation and Safety

Kum Fai Yuen has contributed to a range of frequently targeted publication venues, publishing multiple works in:

  • Transport Policy
  • Technology in Society
  • Marine Policy
  • Journal of Retailing and Consumer Services
  • International Journal of Environmental Research and Public Health

The scientist has collaborated most often with the following researchers:

  • Xueqin Wang
  • Yiik Diew Wong
  • Xue Li
  • Ruobin Gao
  • Le Yi Koh

Among their recent papers are several influential studies, such as:

  • "The Psychological Causes of Panic Buying Following a Health Crisis," 2020, International Journal of Environmental Research and Public Health
  • "Factors influencing autonomous vehicle adoption: an application of the technology acceptance model and innovation diffusion theory," 2020, Technology Analysis and Strategic Management
  • "The determinants of public acceptance of autonomous vehicles: An innovation diffusion perspective," 2020, Journal of Cleaner Production
  • "Walrus optimizer: A novel nature-inspired metaheuristic algorithm," 2023, Expert Systems with Applications
  • "The Determinants of Panic Buying during COVID-19," 2021, International Journal of Environmental Research and Public Health

Best Publications

  • The Psychological Causes of Panic Buying Following a Health Crisis.

    Kum Fai Yuen;Xueqin Wang;Xueqin Wang;Fei Ma;Kevin X. Li

  • Factors influencing autonomous vehicle adoption: an application of the technology acceptance model and innovation diffusion theory

    Kum Fai Yuen;Lanhui Cai;Guanqiu Qi;Xueqin Wang

  • An investigation of customers’ intention to use self-collection services for last-mile delivery

    Kum Fai Yuen;Xueqin Wang;Li Ting Wendy Ng;Yiik Diew Wong

  • The determinants of public acceptance of autonomous vehicles: An innovation diffusion perspective

    Kum Fai Yuen;Yiik Diew Wong;Fei Ma;Xueqin Wang

  • Walrus optimizer: A novel nature-inspired metaheuristic algorithm

    Unknown

  • An innovation diffusion perspective of e-consumers’ initial adoption of self-collection service via automated parcel station

    Xueqin Wang;Kum Fai Yuen;Yiik Diew Wong;Chee Chong Teo

  • Service quality and customer satisfaction in liner shipping

    Kum Fai Yuen;Vinh Van Thai

  • A fuzzy and Bayesian network CREAM model for human reliability analysis – The case of tanker shipping

    Qingji Zhou;Yiik Diew Wong;Hui Shan Loh;Kum Fai Yuen

  • Factors Influencing the Adoption of Shared Autonomous Vehicles.

    Kum Fai Yuen;Do Thi Khanh Huyen;Xueqin Wang;Guanqiu Qi

  • Carbon Emission Trading Scheme in the shipping sector: Drivers, challenges, and impacts

    Unknown

  • What influences panic buying behaviour? A model based on dual-system theory and stimulus-organism-response framework

    Xue Li;Yusheng Zhou;Yiik Diew Wong;Xueqin Wang

  • Assessment of port resilience using Bayesian network: A study of strategies to enhance readiness and response capacities

    Unknown

  • Exploring consumers’ usage intention of reusable express packaging: An extended norm activation model

    Unknown

  • Adoption of shopper-facing technologies under social distancing: A conceptualisation and an interplay between task-technology fit and technology trust

    Xueqin Wang;Yiik Diew Wong;Tianyi Chen;Kum Fai Yuen

  • Random vector functional link neural network based ensemble deep learning for short-term load forecasting.

    Ruobin Gao;Liang Du;Ponnuthurai N. Suganthan;Qin Zhou

  • Holistic risk assessment of container shipping service based on Bayesian Network Modelling

    Unknown

  • Consumer's usage of logistics technologies: Integration of habit into the unified theory of acceptance and use of technology

    Lanhui Cai;Kum Fai Yuen;Diancen Xie;Mingjie Fang

  • Impact of maritime emissions trading system on fleet deployment and mitigation of CO2 emission

    Mo Zhu;Kum Fai Yuen;Jia Wei Ge;Kevin X. Li

  • Explore public acceptance of autonomous buses: An integrated model of UTAUT, TTF and trust

    Unknown

  • Barriers to supply chain integration in the maritime logistics industry

    Kum Fai Yuen;Vinh Thai

  • The influence of supply chain integration on operational performance: A comparison between product and service supply chains

    Kum Fai Yuen;Vinh Van Thai

  • Understanding Public Acceptance of Autonomous Vehicles Using the Theory of Planned Behaviour.

    Kum Fai Yuen;Grace Chua;Xueqin Wang;Fei Ma

  • Addressing the epistemic uncertainty in maritime accidents modelling using Bayesian network with interval probabilities

    Guizhen Zhang;Vinh V. Thai;Kum Fai Yuen;Hui Shan Loh

  • Assessing the National Logistics System of Vietnam

    Ruth Banomyong;Vinh Vinh Thai;Kumfai Yuen

  • Time series forecasting based on echo state network and empirical wavelet transformation

    Ruobin Gao;Liang Du;Okan Duru;Kum Fai Yuen

  • Fuzzy comprehensive evaluation of port-centric supply chain disruption threats

    Hui Shan Loh;Qingji Zhou;Vinh V. Thai;Yiik Diew Wong

  • Determinants of ship operators’ options for compliance with IMO 2020

    Kevin Li;Min Wu;Xiaohan Gu;Kum Fai Yuen

  • An enhanced CREAM with stakeholder-graded protocols for tanker shipping safety application

    Qingji Zhou;Yiik Diew Wong;Hong Xu;Vinh Van Thai

  • This is not me! Technology-identity concerns in consumers’ acceptance of autonomous vehicle technology

    Xueqin Wang;Xueqin Wang;Yiik Diew Wong;Kevin X. Li;Kum Fai Yuen

  • Assessing the vulnerability of urban rail transit network under heavy air pollution: A dynamic vehicle restriction perspective

    Fei Ma;Yuan Liang;Kum Fai Yuen;Qipeng Sun

Frequent Co-Authors

Yiik Diew Wong
Yiik Diew Wong Nanyang Technological University
Kevin X. Li
Kevin X. Li Zhejiang University
Vinh V. Thai
Vinh V. Thai RMIT University
Guanqiu Qi
Guanqiu Qi Buffalo State University
Adrian Wing-Keung Law
Adrian Wing-Keung Law National University of Singapore
Jiuh-Biing Sheu
Jiuh-Biing Sheu National Taiwan University
Jasmine Siu Lee Lam
Jasmine Siu Lee Lam Technical University of Denmark

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring online degree options can open a wide range of career pathways related to Engineering and Technology. For those interested in management roles within technical fields, an mba in operations management online focuses on optimizing processes, supply chains, and operations—skills vital for modern engineering leaders.

Many professionals seek flexibility, and admissions requirements like standardized tests can be a barrier. Thankfully, you can find strong choices among no gmat online mba degrees, making advanced business education more accessible.

Affordability is another key concern. Programs highlighted as the best online mba under 35k offer quality education at a lower cost, making it easier for students to invest in their future without heavy debt.

Lastly, technical skills in social media and digital marketing are increasingly critical. Earning a social media degree can complement your engineering knowledge, preparing you to lead in digital transformation projects and innovation-driven workplaces.

Best Scientists Citing Kum Fai Yuen

Trending Scientists

Recently Published Articles