Kun Chen

46 papers receiving 731 citations

Peers

Kun Chen
Comparison fields: 5 of 84
  • Management Information Systems 233
  • Information Systems and Management 105
  • Information Systems 294
  • Marketing 98
  • Management Science and Operations Research 90
Replace Victoria L. Lemieux with:
Victoria L. Lemieux Canada
Ling Xue United States
Dan Ma Singapore
Huosong Xia China
Ke‐Wei Huang Singapore
Jianrong Yao China
Qian Tang United States
Liudmila Zavolokina Switzerland
Vasudeva Akula United States
Kun Chen relative to Victoria L. Lemieux Canada Victoria L. Lemieux's profile →
Citations per field
00.5×2×2.6×
Victoria L. Lemieux · 1×
Citations per year

Countries citing papers authored by Kun Chen

Since Specialization
Citations

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

Fields of papers citing papers by Kun Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Kun Chen, 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 Kun Chen Line = papers co-authored together Kun Chen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016185
2 201956
3 202241
4 201641
5 201737
6 201535
7 201832
8 201532
9 201630
10 201530
11 202128
12 202122
13 201522
14 201617
15 202017
16 202316
17 201612
18 201611
19 201810
20 20179

About Kun Chen

Kun Chen is a scholar working on Economics and Econometrics, Management Science and Operations Research, Information Systems, Management Information Systems and Statistical and Nonlinear Physics, having authored 49 papers that have together received 769 indexed citations. Recurring topics across this work include Stock Market Forecasting Methods (12 papers), Complex Systems and Time Series Analysis (10 papers), Complex Network Analysis Techniques (7 papers), Financial Markets and Investment Strategies (6 papers), Digital Marketing and Social Media (6 papers), Blockchain Technology Applications and Security (5 papers), Corporate Finance and Governance (5 papers) and FinTech, Crowdfunding, Digital Finance (4 papers). The work is most often cited by research in Management Information Systems (233 citations), Information Systems and Management (105 citations), Information Systems (294 citations), Marketing (98 citations) and Management Science and Operations Research (90 citations). Kun Chen has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Huaiqing Wang, Dongming Xu, Peng Luo, Xin Li, Yongli Li, Chong Wu, Carol Xiaojuan Ou, Libo Liu, Wei Zhu and Kristijan Mirkovski. Their work appears in journals such as Electronic Commerce Research and Applications, Financial Innovation, Journal of Information Science, Electronic Commerce Research and Information & Management.

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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