Sunju Park

155 papers receiving 2.1k citations

Peers

Sunju Park
Comparison fields: 5 of 175
  • Complementary and alternative medicine 160
  • Industrial and Manufacturing Engineering 149
  • Oncology 367
  • Management Science and Operations Research 139
  • Management Information Systems 91
Replace Huei Lee with:
Huei Lee Taiwan
Yuhong Liu China
Robert Stevens United Kingdom
Minjie Zhang Australia
Hong Wan China
Xiaodi Huang Australia
Huimin Jiang China
Junbo Wang China
Elena Marchiori Netherlands
Jia Liu China
Sunju Park relative to Huei Lee Taiwan Huei Lee's profile →
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Citations per year

Countries citing papers authored by Sunju Park

Since Specialization
Citations

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

Fields of papers citing papers by Sunju Park

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 180 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006157
2 2015137
3 201376
4 202174
5 201770
6 201369
7 201567
8 201166
9 201058
10 201454
11 201649
12 200945
13 201145
14 200744
15 201738
16 201636
17 201632
18 201129
19 202028
20 200328

About Sunju Park

Sunju Park is a scholar working on Information Systems, Complementary and alternative medicine, Pharmacology, Computer Networks and Communications and Marketing, having authored 180 papers that have together received 2.1k indexed citations. Recurring topics across this work include Healthcare and Venom Research (23 papers), Traditional Chinese Medicine Studies (21 papers), Complex Network Analysis Techniques (12 papers), Education and Learning Interventions (10 papers), Complementary and Alternative Medicine Studies (10 papers), Consumer Perception and Purchasing Behavior (9 papers), Auction Theory and Applications (9 papers) and Consumer Market Behavior and Pricing (9 papers). The work is most often cited by research in Complementary and alternative medicine (160 citations), Industrial and Manufacturing Engineering (149 citations), Oncology (367 citations), Management Science and Operations Research (139 citations) and Management Information Systems (91 citations). Sunju Park has collaborated with scholars based in South Korea, United States and Japan. Frequent co-authors include Sang‐Wook Kim, Seong‐Gyu Ko, Shuguang Liu, Lei Lei, Andrzej Ruszczyński, Michael H. Rothkopf, Anders Josefsson, George Sgouros, Kideok Jin and Jessie R. Nedrow. Their work appears in journals such as Medicine, Cancer Research, Evidence-based Complementary and Alternative Medicine, Information Sciences and Trials.

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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