Yi-ting Wang

21 papers receiving 304 citations

Peers

Yi-ting Wang
Comparison fields: 5 of 88
  • Management Science and Operations Research 127
  • Statistics, Probability and Uncertainty 28
  • Finance 35
  • Health Informatics 3
  • Medical Laboratory Technology 3
Replace Arash Ghanbari with:
Arash Ghanbari Iran
Maria Barbati Italy
Bartosz Sawik Poland
João Carlos Lourenço Portugal
Bakhtiar Ostadi Iran
Rongjun Li China
Bahar Biller United States
Ignacy Kaliszewski Poland
Mehmet Ali Cengiz Türkiye
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Citations per year

Countries citing papers authored by Yi-ting Wang

Since Specialization
Citations

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

Fields of papers citing papers by Yi-ting Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yi-ting Wang. 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 Yi-ting Wang. The network helps show where Yi-ting Wang may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202141
2 202037
3 202033
4 202127
5 202026
6 202225
7 202118
8
Manager Attributes and Fund Performance: Evidence from Taiwan
201213
9 202212
10 202011
11 202310
12 20229
13 20219
14 20208
15 20238
16 20217
17 20236
18 20226
19 20234
20 20243

About Yi-ting Wang

Yi-ting Wang is a scholar working on Management Science and Operations Research, Artificial Intelligence, Control and Systems Engineering, Finance and Computational Theory and Mathematics, having authored 21 papers that have together received 316 indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (7 papers), Risk and Safety Analysis (3 papers), Rough Sets and Fuzzy Logic (3 papers), Healthcare Systems and Reforms (3 papers), Advanced Clustering Algorithms Research (2 papers), Optimization and Mathematical Programming (2 papers), Healthcare Policy and Management (2 papers) and Artificial Intelligence in Healthcare (2 papers). The work is most often cited by research in Management Science and Operations Research (127 citations), Statistics, Probability and Uncertainty (28 citations), Finance (35 citations), Health Informatics (3 citations) and Medical Laboratory Technology (3 citations). Yi-ting Wang has collaborated with scholars based in China, Singapore and Italy. Frequent co-authors include Jian‐qiang Wang, Pengfei Cheng, Xiaokang Wang, Juan‐juan Peng, Muhammad Shafiq, Shah Nazir, Lin Li, Jin‐Li Hu, Ting Chen and Lin Li. Their work appears in journals such as Journal of the Operational Research Society, Computers & Industrial Engineering, BioMed Research International, International Journal of Environmental Research and Public Health and PLoS ONE.

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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