Li‐Chen Cheng

45 papers receiving 722 citations

Peers

Li‐Chen Cheng
Comparison fields: 5 of 96
  • Management Science and Operations Research 170
  • Information Systems 307
  • Computer Science Applications 55
  • Marketing 74
  • Artificial Intelligence 255
Replace Yongmoo Suh with:
Yongmoo Suh South Korea
Hyea Kyeong Kim South Korea
Nurfadhlina Mohd Sharef Malaysia
Hongke Zhao China
Jesus Serrano‐Guerrero Spain
Longqi Yang United States
Tony Cheng-Kui Huang Taiwan
Álvaro Tejeda-Lorente Spain
Rishabh Mehrotra United Kingdom
Li‐Chen Cheng relative to Yongmoo Suh South Korea Yongmoo Suh's profile →
Citations per field
00.5×1.5×2.3×
Yongmoo Suh · 1×
Citations per year

Countries citing papers authored by Li‐Chen Cheng

Since Specialization
Citations

This map shows the geographic impact of Li‐Chen Cheng'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 Li‐Chen Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Li‐Chen Cheng more than expected).

Fields of papers citing papers by Li‐Chen Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Li‐Chen Cheng. 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 Li‐Chen Cheng. The network helps show where Li‐Chen Cheng may publish in the future.

Co-authors

The 22 scholars most cited alongside Li‐Chen Cheng, 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 Li‐Chen Cheng Line = papers co-authored together Li‐Chen Cheng links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007120
2 201359
3 201943
4 201842
5 200940
6 202136
7 200833
8 201630
9 200729
10 202226
11 201125
12 202124
13 201722
14 201822
15 202319
16 201919
17 201818
18 202116
19 202315
20 202415

About Li‐Chen Cheng

Li‐Chen Cheng is a scholar working on Information Systems, Sociology and Political Science, Artificial Intelligence, Management Science and Operations Research and Signal Processing, having authored 46 papers that have together received 762 indexed citations. Recurring topics across this work include Digital Marketing and Social Media (12 papers), Sentiment Analysis and Opinion Mining (10 papers), Recommender Systems and Techniques (10 papers), Data Management and Algorithms (7 papers), Multi-Criteria Decision Making (5 papers), Customer Service Quality and Loyalty (4 papers), Stock Market Forecasting Methods (4 papers) and Spam and Phishing Detection (4 papers). The work is most often cited by research in Management Science and Operations Research (170 citations), Information Systems (307 citations), Computer Science Applications (55 citations), Marketing (74 citations) and Artificial Intelligence (255 citations). Li‐Chen Cheng has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Yen‐Liang Chen, Ching‐Nan Chuang, Yu-Hsiang Huang, Mu‐En Wu, Kuanchin Chen, Limin Sun, Hui‐Chun Chu, Chi‐Lun Huang, Judy C. R. Tseng and Ya‐Han Hu. Their work appears in journals such as Decision Support Systems, Journal of Global Information Management, Electronic Commerce Research, Interactive Learning Environments and Expert Systems with Applications.

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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