World's Best Scientists 2026 revealed!

D-Index & Metrics

Business and Management

D-Index
71
Citations
17253
World Ranking
289
National Ranking
19

Computer Science

D-Index
69
Citations
16252
World Ranking
1997
National Ranking
276

Kwai-Sang Chin 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 Kwai-Sang Chin 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: 293 publications — 91st percentile

91% of scientists in this discipline score the same or lower.

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

Kwai-Sang Chin 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 Kwai-Sang Chin 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: 71 D-Index — 91st percentile

91% of scientists in this discipline score the same or lower.

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

Overview

Kwai-Sang Chin is affiliated with the City University of Hong Kong in China. Their research primarily spans the fields of Business, Management and Accounting, as well as Engineering. Within these broader areas, their work focuses significantly on subfields such as Management Science and Operations Research, Artificial Intelligence, Strategy and Management, Management Information Systems, and Industrial and Manufacturing Engineering.

The researcher has contributed extensively to topics including Multi-Criteria Decision Making, Supply Chain and Inventory Management, Sustainable Supply Chain Management, Transportation Planning and Optimization, Consumer Market Behavior and Pricing, Rough Sets and Fuzzy Logic, and Sentiment Analysis and Opinion Mining.

Frequent coauthors collaborating with Kwai-Sang Chin include Zhen-Song Chen, Witold Pedrycz, Kannan Govindan, Luis Martínez, and Xiaohong Pan.

Their publications are often found in scholarly venues such as Expert Systems with Applications, Applied Soft Computing, Information Sciences, SSRN Electronic Journal, and Transportation Research Part B Methodological. Notably, three publications have appeared in each of Expert Systems with Applications, Applied Soft Computing, and Information Sciences, with two publications in Transportation Research Part B Methodological.

Recent papers by Kwai-Sang Chin include:

  • Online-review analysis based large-scale group decision-making for determining passenger demands and evaluating passenger satisfaction: Case study of high-speed rail system in China (2020, Information Fusion)
  • Third-party reverse logistics provider selection: A computational semantic analysis-based multi-perspective multi-attribute decision-making approach (2020, Expert Systems with Applications)
  • Hotel selection driven by online textual reviews: Applying a semantic partitioned sentiment dictionary and evidence theory (2020, International Journal of Hospitality Management)
  • An actor-critic deep reinforcement learning approach for metro train scheduling with rolling stock circulation under stochastic demand (2020, Transportation Research Part B Methodological)
  • Sustainable building material selection: An integrated multi-criteria large group decision making framework (2021, Applied Soft Computing)

Best Publications

  • Risk evaluation in failure mode and effects analysis using fuzzy weighted geometric mean

    Ying-Ming Wang;Kwai-Sang Chin;Gary Ka Kwai Poon;Jian-Bo Yang

  • Identifying and prioritizing critical success factors for coopetition strategy

    Kwai‐Sang Chin;Boris L. Chan;Ping‐Kit Lam

  • On the centroids of fuzzy numbers

    Ying-Ming Wang;Jian-Bo Yang;Dong-Ling Xu;Kwai-Sang Chin

  • The evidential reasoning approach for MADA under both probabilistic and fuzzy uncertainties

    Jian-Bo Yang;Jian-Bo Yang;Y. M. Wang;Y. M. Wang;Dong-Ling Xu;Kwai-Sang Chin

  • Failure mode and effects analysis using a group-based evidential reasoning approach

    Kwai-Sang Chin;Ying-Ming Wang;Gary Ka Kwai Poon;Jian-Bo Yang

  • A NEW METHOD FOR MEASURING UNCERTAINTY AND FUZZINESS IN ROUGH SET THEORY

    Jiye Liang;Kwai-Sang Chin;Chuangyin Dang;Richard C. M. Yam

  • Fuzzy analytic hierarchy process: A logarithmic fuzzy preference programming methodology

    Unknown

  • A neutral DEA model for cross-efficiency evaluation and its extension

    Ying-Ming Wang;Kwai-Sang Chin

  • The evidential reasoning approach for multiple attribute decision analysis using interval belief degrees

    Ying Ming Wang;Ying Ming Wang;Ying Ming Wang;Jian Bo Yang;Dong Ling Xu;Kwai Sang Chin

  • Failure mode and effects analysis by data envelopment analysis

    Kwai-Sang Chin;Ying-Ming Wang;Gary Ka Kwai Poon;Jian-Bo Yang

  • Development of a fuzzy FMEA based product design system

    Kwai Sang Chin;Allen Chan;Jian Bo Yang

  • Some alternative models for DEA cross-efficiency evaluation

    Ying-Ming Wang;Kwai-Sang Chin

  • Identifying and prioritizing critical success factors for conflict management in collaborative new product development

    Ping-Kit Lam;Kwai-Sang Chin

  • Proportional hesitant fuzzy linguistic term set for multiple criteria group decision making

    Zhen-Song Chen;Kwai-Sang Chin;Yan-Lai Li;Yi Yang

  • Technology transfer and innovation performance: Evidence from Chinese firms

    Jian Cheng Guan;Chiu Kam Mok;Richard C.M. Yam;K.S. Chin

  • Assessing new product development project risk by Bayesian network with a systematic probability generation methodology

    Kwai-Sang Chin;Da-Wei Tang;Jian-Bo Yang;Shui Yee Wong

  • A proposed framework for implementing TQM in Chinese organizations

    Kwai‐Sang Chin;Kit‐Fai Pun

  • An AHP based study of critical factors for TQM implementation in Shanghai manufacturing industries

    K.-S. Chin;K.-F. Pun;Y. Xu;J.S.F. Chan

  • Online-review analysis based large-scale group decision-making for determining passenger demands and evaluating passenger satisfaction: Case study of high-speed rail system in China

    Zhen-Song Chen;Zhen-Song Chen;Xiao-Lu Liu;Kwai-Sang Chin;Witold Pedrycz

  • A review of the Chinese cultural influences on Chinese enterprise management

    Kit-Fai Pun;Kwai-Sang Chin;Henry Lau

  • A study on supply chain management practices: The Hong Kong manufacturing perspective

    Kwai‐Sang Chin;V.M. Rao Tummala;Jendy P.F. Leung;Xiaoqing Tang

  • An evaluation of success factors using the AHP to implement ISO 14001‐based EMS

    Kwai‐Sang Chin;Simon Chiu;V.M. Rao Tummala

Frequent Co-Authors

Ying-Ming Wang
Ying-Ming Wang Fuzhou University
Zhen-Song Chen
Zhen-Song Chen Wuhan University
Jian-Bo Yang
Jian-Bo Yang University of Manchester
Kit Fai Pun
Kit Fai Pun University of the West Indies
Kwok-Leung Tsui
Kwok-Leung Tsui Virginia Tech
Henry C. W. Lau
Henry C. W. Lau Western Sydney University
Luis Martínez
Luis Martínez University of Jaén
Dong-Ling Xu
Dong-Ling Xu University of Manchester
Prasad Yarlagadda
Prasad Yarlagadda Queensland University of Technology
Richard C.M. Yam
Richard C.M. Yam City University of Hong Kong

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