Keebom Kang

32 papers receiving 271 citations

Peers

Keebom Kang
Comparison fields: 5 of 46
  • Management Science and Operations Research 185
  • Statistics, Probability and Uncertainty 88
  • Statistics and Probability 83
  • Management Information Systems 68
  • Industrial and Manufacturing Engineering 42
Replace Shuming Wang with:
Shuming Wang Japan
Ikuo Arizono Japan
Masamitsu Ohnishi Japan
Suyan Teng Singapore
Jinhua Cao Taiwan
Emily K. Lada United States
Jane N. Hagstrom United States
Stella Kapodistria Netherlands
Zhaolin Hu China
Susan R. Hunter United States
Keebom Kang relative to Shuming Wang Japan Shuming Wang's profile →
Citations per field
00.5×4.5×
Shuming Wang · 1×
Citations per year

Countries citing papers authored by Keebom Kang

Since Specialization
Citations

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

Fields of papers citing papers by Keebom Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 12 scholars most cited alongside Keebom Kang, 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 Keebom Kang Line = papers co-authored together Keebom Kang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199253
2 199936
3 198720
4 199018
5 199015
6 200113
7 200312
8 200611
9 200611
10 199710
11 200210
12 20079
13
A decision support model for valuing proposed improvements in component reliability
20059
14 19869
15 20107
16
CONFIDENCE INTERVAL ESTIMATION VIA BATCH MEANS AND TIME SERIES MODELING
19847
17 20107
18 20106
19 19856
20 19914

About Keebom Kang

Keebom Kang is a scholar working on Management Science and Operations Research, Safety, Risk, Reliability and Quality, Statistics, Probability and Uncertainty, Management Information Systems and Control and Systems Engineering, having authored 37 papers that have together received 297 indexed citations. Recurring topics across this work include Simulation Techniques and Applications (19 papers), Technology Assessment and Management (8 papers), Advanced Statistical Process Monitoring (7 papers), Advanced Queuing Theory Analysis (4 papers), Advanced Manufacturing and Logistics Optimization (4 papers), Reliability and Maintenance Optimization (4 papers), Modeling, Simulation, and Optimization (4 papers) and Systems Engineering Methodologies and Applications (3 papers). The work is most often cited by research in Management Science and Operations Research (185 citations), Statistics, Probability and Uncertainty (88 citations), Statistics and Probability (83 citations), Management Information Systems (68 citations) and Industrial and Manufacturing Engineering (42 citations). Keebom Kang has collaborated with scholars based in United States, Brazil and South Korea. Frequent co-authors include David Goldsman, Bruce W. Schmeiser, Kevin R. Gue, Andrew F. Seila, Kenneth H. Doerr, Susan M. Sanchez, D. R. Eaton, Uday Apte, Robert G. Sargent and Seong‐Hee Kim. Their work appears in journals such as Operations Research, Naval Research Logistics (NRL), International Journal of Technology Management, Operations Research Letters and Quality Engineering.

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.

Explore authors with similar magnitude of impact