Cuicui Luo

1.1k citations
50 papers · 736 · h-index 15

Impact in

Papers in

Cuicui Luo

38 papers receiving 714 citations

Peers

Cuicui Luo
Comparison fields: 5 of 93
  • Accounting 170
  • Management Science and Operations Research 151
  • Finance 73
  • Management Information Systems 71
  • General Energy 7
Replace Rongda Chen with:
Rongda Chen China
Desheng Dash Wu China
You Zhu China
Elena Fedorova Russia
Farimah Mokhatab Rafiei Iran
Shaw K. Chen United States
Guotai Chi China
Kao-Yi Shen Taiwan
Jamal Ouenniche United Kingdom
Cuicui Luo relative to Rongda Chen China Rongda Chen's profile →
Citations per field
00.5×2×2.7×
Rongda Chen · 1×
Citations per year

Countries citing papers authored by Cuicui Luo

Since Specialization
Citations

This map shows the geographic impact of Cuicui Luo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Cuicui Luo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cuicui Luo more than expected).

Fields of papers citing papers by Cuicui Luo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cuicui Luo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Cuicui Luo. The network helps show where Cuicui Luo may publish in the future.

Co-authors

The 25 scholars most cited alongside Cuicui Luo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Cuicui Luo Line = papers co-authored together Cuicui Luo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016150
2 201677
3 201451
4 202050
5 201446
6 201835
7 201930
8 201925
9 201423
10 202222
11 201519
12 202518
13 202218
14 202316
15 201515
16 202315
17 202315
18 202215
19 200014
20 201813

About Cuicui Luo

Cuicui Luo is a scholar working on Management Science and Operations Research, Artificial Intelligence, Accounting, Finance and Economics and Econometrics, having authored 50 papers that have together received 736 indexed citations. Recurring topics across this work include Financial Distress and Bankruptcy Prediction (6 papers), Imbalanced Data Classification Techniques (6 papers), Multi-Criteria Decision Making (5 papers), Market Dynamics and Volatility (5 papers), Advanced Graph Neural Networks (5 papers), Efficiency Analysis Using DEA (4 papers), Face and Expression Recognition (3 papers) and Anomaly Detection Techniques and Applications (3 papers). The work is most often cited by research in Accounting (170 citations), Management Science and Operations Research (151 citations), Finance (73 citations), Management Information Systems (71 citations) and General Energy (7 citations). Cuicui Luo has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Desheng Dash Wu, Dexiang Wu, Can Wei, David L. Olson, John R. Birge, Luis Seco, Yuchen Pan, Alexandre B. Dolgui, James H. Lambert and Desheng Dash Wu. Their work appears in journals such as Neurocomputing, Information Processing & Management, IEEE Transactions on Systems Man and Cybernetics Systems, IEEE Systems Journal and Risk Analysis.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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