World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
58
Citations
11145
World Ranking
3689
National Ranking
493

Zhi-Ping Fan publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Zhi-Ping Fan sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 189 publications — 42nd percentile

42% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Zhi-Ping Fan D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Zhi-Ping Fan sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 58 D-Index — 75th percentile

75% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Zhi-Ping Fan is affiliated with Northeastern University in China and has a significant body of research in the areas of business, management, and engineering. Their work addresses various topics such as supply chain and inventory management, consumer market behavior, pricing strategies, and the application of blockchain technology.

Their research contributions span several subfields, including marketing, management information systems, strategy and management, automotive engineering, as well as sociology and political science.

Key topics covered by their research include:

  • Supply Chain and Inventory Management
  • Consumer Market Behavior and Pricing
  • Transportation and Mobility Innovations
  • Sustainable Supply Chain Management
  • Blockchain Technology Applications and Security
  • Sharing Economy and Platforms
  • Electric Vehicles and Infrastructure

Some of Zhi-Ping Fan's recent publications include:

  • "Considering the traceability awareness of consumers: should the supply chain adopt the blockchain technology?", 2020, Annals of Operations Research
  • "An analysis of strategies for adopting blockchain technology in the fresh product supply chain", 2021, International Journal of Production Research
  • "Green subsidy modes and pricing strategy in a capital-constrained supply chain", 2020, Transportation Research Part E Logistics and Transportation Review
  • "Tourism demand forecasting with time series imaging: A deep learning model", 2021, Annals of Tourism Research
  • "Processes and methods of information fusion for ranking products based on online reviews: An overview", 2020, Information Fusion

Zhi-Ping Fan has frequently published in multiple respected journals, which include:

  • International Transactions in Operational Research
  • Transportation Research Part E Logistics and Transportation Review
  • Computers & Industrial Engineering
  • European Journal of Operational Research
  • International Journal of Production Research

The scientist has collaborated extensively with several coauthors over multiple projects. Notable frequent collaborators are:

  • Minghe Sun
  • Zhongwei Chen
  • Xiaohuan Wang
  • Zhong Du
  • Xue-Yan Wu

In addition to journal articles, Zhi-Ping Fan has published books, including a contribution to the book titled Advances in Simulation and Process Modelling published by Springer Nature in 2021.

Best Publications

  • A subjective and objective integrated approach to determine attribute weights

    Jian Ma;Zhi-Ping Fan;Li-Hua Huang

  • Ranking products through online reviews

    Yang Liu;Jian-Wu Bi;Zhi-Ping Fan

  • An approach to multiple attribute decision making based on fuzzy preference information on alternatives

    Zhi-Ping Fan;Jian Ma;Quan Zhang

  • Product sales forecasting using online reviews and historical sales data: A method combining the Bass model and sentiment analysis

    Zhi-Ping Fan;Yu-Jie Che;Zhen-Yu Chen

  • Wisdom of crowds: Conducting importance-performance analysis (IPA) through online reviews

    Jian-Wu Bi;Yang Liu;Zhi-Ping Fan;Jin Zhang

  • A method for repairing the inconsistency of fuzzy preference relations

    Jian Ma;Zhi-Ping Fan;Yan-Ping Jiang;Ji-Ye Mao

  • A method for group decision making with multi-granularity linguistic assessment information

    Yan-Ping Jiang;Zhi-Ping Fan;Jian Ma

  • Risk decision analysis in emergency response: A method based on cumulative prospect theory

    Yang Liu;Zhi-Ping Fan;Yao Zhang

  • Multi-class sentiment classification

    Yang Liu;Jian-Wu Bi;Zhi-Ping Fan

  • Extended TODIM method for hybrid multiple attribute decision making problems

    Zhi-Ping Fan;Xiao Zhang;Fa-Dong Chen;Yang Liu

  • Modelling customer satisfaction from online reviews using ensemble neural network and effect-based Kano model

    Jian-Wu Bi;Yang Liu;Zhi-Ping Fan;Erik Cambria

  • A method for multi-class sentiment classification based on an improved one-vs-one (OVO) strategy and the support vector machine (SVM) algorithm

    Yang Liu;Jian-Wu Bi;Zhi-Ping Fan

  • Ranking L-R fuzzy number based on deviation degree

    Zhong-Xing Wang;Yong-Jun Liu;Zhi-Ping Fan;Bo Feng

  • Considering the traceability awareness of consumers: should the supply chain adopt the blockchain technology?

    Zhi-Ping Fan;Xue-Yan Wu;Bing-Bing Cao

  • A method for group decision-making based on multi-granularity uncertain linguistic information

    Zhi-Ping Fan;Yang Liu

  • A goal programming approach to group decision making based on multiplicative preference relations and fuzzy preference relations

    Zhi-Ping Fan;Jian Ma;Yan-Ping Jiang;Yong-Hong Sun

  • A hierarchical multiple kernel support vector machine for customer churn prediction using longitudinal behavioral data

    Zhen Yu Chen;Zhi Ping Fan;Minghe Sun

  • An analysis of strategies for adopting blockchain technology in the fresh product supply chain

    Xue-Yan Wu;Zhi-Ping Fan;Bing-Bing Cao

  • An optimization method for selecting project risk response strategies

    Yao Zhang;Zhi-Ping Fan

  • Evaluating knowledge management capability of organizations: a fuzzy linguistic method

    Zhi-Ping Fan;Bo Feng;Yong-Hong Sun;Wei Ou

  • A method for large group decision-making based on evaluation information provided by participators from multiple groups

    Yang Liu;Zhi-Ping Fan;Xiao Zhang

Frequent Co-Authors

Jian Ma
Jian Ma City University of Hong Kong
Jiafu Tang
Jiafu Tang Dongbei University of Finance and Economics
Ying-Ming Wang
Ying-Ming Wang Fuzhou University
Erik Cambria
Erik Cambria Nanyang Technological University
W. H. Ip
W. H. Ip Hong Kong Polytechnic University
Yucheng Dong
Yucheng Dong Sichuan University
Dingwei Wang
Dingwei Wang Northeastern University
Shu-Cherng Fang
Shu-Cherng Fang North Carolina State University
Zhongsheng Hua
Zhongsheng Hua Zhejiang University
Bo Xu
Bo Xu Nanjing University of Science and Technology

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