Guan Jun Wang

706 citations
28 papers · 559 · h-index 14

Impact in

Papers in

Guan Jun Wang

27 papers receiving 538 citations

Peers

Guan Jun Wang
Comparison fields: 5 of 47
  • Software 282
  • Safety, Risk, Reliability and Quality 518
  • Statistics and Probability 344
  • Statistics, Probability and Uncertainty 163
  • Management Information Systems 50
Replace Delia Montoro‐Cazorla with:
Delia Montoro‐Cazorla Spain
William Murdock United States
Wagner de Souza Borges Brazil
Chang Hoon Lie South Korea
Hidenori Morimura Japan
P.P. Gupta India
Laurent Bordes France
Joseph C. Hudson United States
F. Rivas-Dávalos Mexico
Shreekant Varshney India
Guan Jun Wang relative to Delia Montoro‐Cazorla Spain Delia Montoro‐Cazorla's profile →
Citations per field
00.5×2.5×
Delia Montoro‐Cazorla · 1×
Citations per year

Countries citing papers authored by Guan Jun Wang

Since Specialization
Citations

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

Fields of papers citing papers by Guan Jun Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Guan Jun 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 Guan Jun Wang. The network helps show where Guan Jun Wang may publish in the future.

Co-authors

The 6 scholars most cited alongside Guan Jun 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 Guan Jun Wang Line = papers co-authored together Guan Jun Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200593
2 200673
3 200946
4 201235
5 201428
6 200627
7 200725
8 200625
9 201722
10 200822
11 200919
12 201119
13 201616
14 201516
15 201013
16 201612
17 201112
18 201411
19 201011
20 200411

About Guan Jun Wang

Guan Jun Wang is a scholar working on Safety, Risk, Reliability and Quality, Statistics and Probability, Software, Statistics, Probability and Uncertainty and Strategy and Management, having authored 28 papers that have together received 559 indexed citations. Recurring topics across this work include Reliability and Maintenance Optimization (23 papers), Statistical Distribution Estimation and Applications (21 papers), Software Reliability and Analysis Research (20 papers), Corporate Taxation and Avoidance (2 papers), Financial Reporting and Valuation Research (2 papers), Probabilistic and Robust Engineering Design (2 papers), Risk and Safety Analysis (2 papers) and Fiscal Policy and Economic Growth (2 papers). The work is most often cited by research in Software (282 citations), Safety, Risk, Reliability and Quality (518 citations), Statistics and Probability (344 citations), Statistics, Probability and Uncertainty (163 citations) and Management Information Systems (50 citations). Guan Jun Wang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Yuan Lin Zhang, Richard C.M. Yam, Rui Peng, Jacques Beaumont, Qiang Li and Bo Qian. Their work appears in journals such as Applied Mathematical Modelling, International Journal of Systems Science, International Journal of Systems Science Operations & Logistics, European Journal of Operational Research and Applied Mathematics and Computation.

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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