K. Paul Yoon

969 total citations
13 papers, 740 citations indexed

About

K. Paul Yoon is a scholar working on Management Science and Operations Research, Control and Systems Engineering and Management Information Systems. According to data from OpenAlex, K. Paul Yoon has authored 13 papers receiving a total of 740 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Management Science and Operations Research, 5 papers in Control and Systems Engineering and 4 papers in Management Information Systems. Recurrent topics in K. Paul Yoon's work include Multi-Criteria Decision Making (5 papers), Optimization and Mathematical Programming (4 papers) and Supply Chain and Inventory Management (3 papers). K. Paul Yoon is often cited by papers focused on Multi-Criteria Decision Making (5 papers), Optimization and Mathematical Programming (4 papers) and Supply Chain and Inventory Management (3 papers). K. Paul Yoon collaborates with scholars based in United States and South Korea. K. Paul Yoon's co-authors include Srinivas Talluri, Abu S. M. Masud, C. L. Hwang, Mohammad Ali Sedaghat, Won Kyung Kim, Yong-Beom Kim, Lotfi Tadj, Jae‐Yong Kim and Chiehyeon Lim and has published in prestigious journals such as Expert Systems with Applications, International Journal of Production Economics and Fuzzy Sets and Systems.

In The Last Decade

K. Paul Yoon

13 papers receiving 672 citations

Peers

K. Paul Yoon

MSOR

CSE

MIS

SM

SP

Ming-Shin Kuo Taiwan

Jeffrey L. Ringuest United States

Bijan Sarkar India

Tsung-Han Chang Taiwan

Erhan Bozdag Türkiye

Kajal Chatterjee India

Mališa Žižović Serbia

Luís Alberto Duncan Rangel Brazil

Masatake Nagai Japan

Hsien-Da Lee Taiwan

Ming-Shin Kuo Taiwan

K. Paul Yoon

532 ×1.4

MSOR

143 ×0.8

CSE

62 ×0.6

MIS

121 ×1.3

SM

68 ×0.8

SP

Citations per year, relative to K. Paul Yoon K. Paul Yoon (= 1×) peers Ming-Shin Kuo

Countries citing papers authored by K. Paul Yoon

Since Specialization

Citations

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

Fields of papers citing papers by K. Paul Yoon

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by K. Paul Yoon. 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 K. Paul Yoon. The network helps show where K. Paul Yoon may publish in the future.

Co-authorship network of co-authors of K. Paul Yoon

This figure shows the co-authorship network connecting the top 25 collaborators of K. Paul Yoon. A scholar is included among the top collaborators of K. Paul Yoon based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with K. Paul Yoon. K. Paul Yoon is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

13 of 13 papers shown

1.

Yoon, K. Paul, et al.. (2023). MMP Net: A feedforward neural network model with sequential inputs for representing continuous multistage manufacturing processes without intermediate outputs. IISE Transactions. 56(10). 1058–1069. 5 indexed citations

2.

Yoon, K. Paul, et al.. (2021). Portfolio Selection by the Axiom of Choice: Post Mean-Variance Analysis. 26(2). 303–303. 1 indexed citations

3.

Yoon, K. Paul & Mohammad Ali Sedaghat. (2020). Rank Power Analysis For Comparative Strength Of Professional Sports Franchises. Journal of Applied Business Research (JABR). 36(4). 181–196. 2 indexed citations

4.

Yoon, K. Paul, et al.. (2017). The behavioral TOPSIS. Expert Systems with Applications. 89. 266–272. 128 indexed citations

5.

Tadj, Lotfi & K. Paul Yoon. (2014). Binomial Schedule for an M/G/1 Type Queueing System with an Unreliable Server under N-Policy. Advances in Decision Sciences. 2014. 1–6. 1 indexed citations

6.

Sedaghat, Mohammad Ali, et al.. (2011). Queuing Models To Balance Systems With Excess Supply. International Business & Economics Research Journal (IBER). 8(1). 6 indexed citations

7.

Kim, Won Kyung, et al.. (2011). Improving system performance for stochastic activity network: A simulation approach. Computers & Industrial Engineering. 62(1). 1–12. 6 indexed citations

8.

Yoon, K. Paul, et al.. (2010). Simulation model for extended double-ended queueing. Computers & Industrial Engineering. 59(2). 209–219. 14 indexed citations

9.

Talluri, Srinivas & K. Paul Yoon. (2000). A cone-ratio DEA approach for AMT justification. International Journal of Production Economics. 66(2). 119–129. 92 indexed citations

10.

Yoon, K. Paul, et al.. (1997). Identifying investment opportunities for advanced manufacturing systems with comparative-integrated performance measurement. International Journal of Production Economics. 50(1). 23–33. 225 indexed citations

11.

Yoon, K. Paul. (1996). A probabilistic approach to rank complex fuzzy numbers. Fuzzy Sets and Systems. 80(2). 167–176. 63 indexed citations

12.

Yoon, K. Paul, et al.. (1994). A Make‐or‐Buy Decision Analysis Involving Imprecise Data. International Journal of Operations & Production Management. 14(2). 62–69. 37 indexed citations

13.

Hwang, C. L., et al.. (1980). Mathematical programming with multiple objectives: A tutorial. Computers & Operations Research. 7(1-2). 5–31. 160 indexed citations

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