Jun Ye

542 citations
33 papers · 388 · h-index 10

Impact in

Papers in

Jun Ye

29 papers receiving 369 citations

Peers

Jun Ye
Comparison fields: 5 of 104
  • Organizational Behavior and Human Resource Management 103
  • Marketing 84
  • Developmental Neuroscience 14
  • Strategy and Management 46
  • Information Systems and Management 21
Replace Jing Long with:
Jing Long China
Kuo-Ching Wang Taiwan
Bráulio Alturas Portugal
Tobias Keim Germany
Rajendra Sahu India
Yiming Ma China
Christian Hauser Switzerland
Alrence Halibas Vietnam
Ravindra Jain India
Jun Ye relative to Jing Long China Jing Long's profile →
Citations per field
00.5×4.2×
Jing Long · 1×
Citations per year

Countries citing papers authored by Jun Ye

Since Specialization
Citations

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

Fields of papers citing papers by Jun Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200896
2 200536
3 201035
4 201731
5 201630
6 201828
7 200721
8 201616
9 201214
10 20239
11 20199
12 20219
13 20057
14 20207
15 20166
16 20046
17 20214
18 20124
19 20213
20 20083

About Jun Ye

Jun Ye is a scholar working on Artificial Intelligence, Molecular Biology, Marketing, Sociology and Political Science and Organizational Behavior and Human Resource Management, having authored 33 papers that have together received 388 indexed citations. Recurring topics across this work include Customer Service Quality and Loyalty (5 papers), Angiogenesis and VEGF in Cancer (4 papers), Consumer Behavior in Brand Consumption and Identification (4 papers), Cryptography and Data Security (3 papers), Axon Guidance and Neuronal Signaling (3 papers), Chaos-based Image/Signal Encryption (3 papers), Advanced Steganography and Watermarking Techniques (2 papers) and Environmental Sustainability in Business (2 papers). The work is most often cited by research in Organizational Behavior and Human Resource Management (103 citations), Marketing (84 citations), Developmental Neuroscience (14 citations), Strategy and Management (46 citations) and Information Systems and Management (21 citations). Jun Ye has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Detelina Marinova, Jagdip Singh, J.W. Mark, Xuemin Shen, Yuan Li, Beibei Dong, Ju-Yeon Lee, Nagesh N. Murthy, Sara Hanson and Lan Jiang. Their work appears in journals such as Marketing Letters, Journal of Business Research, International Journal of Oncology, Journal of Consumer Behaviour and IEEE Transactions on Mobile 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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