Hangjun Zhou

512 citations
38 papers · 355 · h-index 9

Impact in

Papers in

Hangjun Zhou

35 papers receiving 327 citations

Peers

Hangjun Zhou
Comparison fields: 5 of 69
  • Management Science and Operations Research 106
  • Accounting 48
  • Management Information Systems 37
  • Artificial Intelligence 114
  • Information Systems 75
Replace Guoxun Wang with:
Guoxun Wang China
Iwona Skalna Poland
Azizul Azhar Ramli Malaysia
Juan Pérez Chile
Shuning Wu China
Yong Chun Shi China
H.S. Wang Taiwan
M.A.H. Farquad India
Hangjun Zhou relative to Guoxun Wang China Guoxun Wang's profile →
Citations per field
00.5×2×3×4×4.5×
Guoxun Wang · 1×
Citations per year

Countries citing papers authored by Hangjun Zhou

Since Specialization
Citations

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

Fields of papers citing papers by Hangjun Zhou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201976
2 202164
3 202040
4 201624
5 201120
6 202218
7 202116
8 202214
9 202113
10 20189
11 20209
12 20188
13 20206
14 20104
15 20184
16 20114
17 20092
18 20142
19 20142
20 20152

About Hangjun Zhou

Hangjun Zhou is a scholar working on Management Science and Operations Research, Information Systems, Computer Networks and Communications, Ecological Modeling and Artificial Intelligence, having authored 38 papers that have together received 355 indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (12 papers), Advanced Decision-Making Techniques (7 papers), Cloud Computing and Resource Management (7 papers), Peer-to-Peer Network Technologies (5 papers), Imbalanced Data Classification Techniques (4 papers), Evaluation Methods in Various Fields (3 papers), Caching and Content Delivery (3 papers) and Rough Sets and Fuzzy Logic (3 papers). The work is most often cited by research in Management Science and Operations Research (106 citations), Accounting (48 citations), Management Information Systems (37 citations), Artificial Intelligence (114 citations) and Information Systems (75 citations). Hangjun Zhou has collaborated with scholars based in China and United States. Frequent co-authors include Sha Fu, Guang Sun, Jing Liu, Xingxing Zhou, Jieyu Zhou, Linli Wang, Ying Gao, Xiaoping Fan, Guang Sun and Shuting Hu. Their work appears in journals such as IEEE Access, Computers, materials & continua/Computers, materials & continua (Print), Scientific Reports, Journal of Applied Sciences and Soft Computing.

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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