Dejing Kong

35 papers receiving 1.0k citations

Peers

Dejing Kong
Comparison fields: 5 of 104
  • Safety, Risk, Reliability and Quality 211
  • Software 81
  • Statistics, Probability and Uncertainty 117
  • Statistics and Probability 102
  • Business and International Management 22
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David G. Robinson United States
Md. Rezaul Karim Bangladesh
Zhiqiang Zhang China
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Citations per field
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Citations per year

Countries citing papers authored by Dejing Kong

Since Specialization
Citations

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

Fields of papers citing papers by Dejing Kong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010399
2 201484
3 201772
4 201971
5 201663
6 201762
7 201757
8 201840
9 202040
10 202022
11 201617
12 201515
13 201811
14 20157
15 20167
16 20145
17 20165
18 20225
19 20255
20
Using A Quality Based Analytic Hierarchy Process To Do Decision-making Analysis In Transportation
20104

About Dejing Kong

Dejing Kong is a scholar working on Safety, Risk, Reliability and Quality, Statistics and Probability, Software, Management Science and Operations Research and Statistics, Probability and Uncertainty, having authored 38 papers that have together received 1.0k indexed citations. Recurring topics across this work include Reliability and Maintenance Optimization (10 papers), Software Reliability and Analysis Research (7 papers), Statistical Distribution Estimation and Applications (6 papers), Multi-Criteria Decision Making (4 papers), Innovation and Knowledge Management (3 papers), Statistical Methods and Inference (3 papers), Innovation Diffusion and Forecasting (3 papers) and Risk and Safety Analysis (3 papers). The work is most often cited by research in Safety, Risk, Reliability and Quality (211 citations), Software (81 citations), Statistics, Probability and Uncertainty (117 citations), Statistics and Probability (102 citations) and Business and International Management (22 citations). Dejing Kong has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Lirong Cui, Qian Gao, Guang Qi, Gongke Zhou, Yingzhen Kong, Ruibo Hu, Yuan Joseph Zhou, Narayanaswamy Balakrishnan, Hongda Gao and Yufei Liu. Their work appears in journals such as Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability, Quality Technology & Quantitative Management, Applied Sciences, Reliability Engineering & System Safety and Technological Forecasting and Social Change.

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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