Won Mo Jang

30 papers receiving 323 citations

Peers

Won Mo Jang
Comparison fields: 5 of 68
  • Modeling and Simulation 42
  • Health 45
  • Applied Psychology 11
  • Clinical Psychology 45
  • Economics and Econometrics 56
Replace Mariali Palacios-Cruz with:
Mariali Palacios-Cruz Mexico
Megan F. Pera United States
Shabnam Iezadi Iran
Jill C. Cash United States
Gianni Corsetti Italy
Titiporn Tuangratananon Thailand
Jeremy Lim Singapore
Héctor Pifarré i Arolas Spain
Aanuoluwapo Adeyimika Afolabi Nigeria
Jeanna-Eve Franck France
Won Mo Jang relative to Mariali Palacios-Cruz Mexico Mariali Palacios-Cruz's profile →
Citations per field
00.5×2×3×4.1×
Mariali Palacios-Cruz · 1×
Citations per year

Countries citing papers authored by Won Mo Jang

Since Specialization
Citations

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

Fields of papers citing papers by Won Mo Jang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Won Mo Jang. 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 Won Mo Jang. The network helps show where Won Mo Jang may publish in the future.

Co-authors

The 25 scholars most cited alongside Won Mo Jang, 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 Won Mo Jang Line = papers co-authored together Won Mo Jang 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 202058
2 202044
3 202141
4 201929
5 201226
6 202118
7 201118
8 202117
9 202113
10 20228
11
Alcohol consumption and the risk of type 2 diabetes mellitus: effect modification by hypercholesterolemia: the Third Korea National Health and Nutrition Examination Survey (2005).
20127
12 20197
13 20236
14 20236
15 20195
16 20135
17 20195
18 20244
19 20233
20 20223

About Won Mo Jang

Won Mo Jang is a scholar working on General Health Professions, Economics and Econometrics, Health, Sociology and Political Science and Oncology, having authored 33 papers that have together received 334 indexed citations. Recurring topics across this work include Patient Satisfaction in Healthcare (5 papers), Healthcare Policy and Management (5 papers), Behavioral Health and Interventions (2 papers), Emergency and Acute Care Studies (2 papers), COVID-19 and Mental Health (2 papers), COVID-19 Pandemic Impacts (2 papers), Vaccine Coverage and Hesitancy (2 papers) and COVID-19 and healthcare impacts (2 papers). The work is most often cited by research in Modeling and Simulation (42 citations), Health (45 citations), Applied Psychology (11 citations), Clinical Psychology (45 citations) and Economics and Econometrics (56 citations). Won Mo Jang has collaborated with scholars based in South Korea, Ethiopia and Puerto Rico. Frequent co-authors include Jin Yong Lee, Sang Jun Eun, Hyemin Jung, Yoon Kim, Sang‐Hyun Cho, Hyun‐Kyung Park, Kwangil Yim, Min Sun Shin, Hye Sook Ahn and Sung Hak Lee. Their work appears in journals such as International Journal of Environmental Research and Public Health, PLoS ONE, Journal of Korean Medical Science, Risk Management and Healthcare Policy and BMJ Open.

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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