Long Liu

33 papers receiving 1.8k citations

Hit Papers

Risk evaluation approaches in failure mode and effects analysis: A literature review 2012 · 669 citations
6692012202620162021200400600

Peers

Long Liu
Comparison fields: 5 of 136
  • Statistics, Probability and Uncertainty 722
  • Management Science and Operations Research 899
  • Medical Laboratory Technology 72
  • Management of Technology and Innovation 274
  • Safety, Risk, Reliability and Quality 338
Replace Kuei‐Hu Chang with:
Kuei‐Hu Chang Taiwan
Metin Çelik Türkiye
Qinglian Lin China
Genbao Zhang China
Samuel Yousefı Iran
Weizhong Wang China
Qiang Su China
Ming‐Hung Shu Taiwan
Rob Basten Netherlands
Ali Fuat Güneri Türkiye
Long Liu relative to Kuei‐Hu Chang Taiwan Kuei‐Hu Chang's profile →
Citations per field
00.5×1.5×2.2×
Kuei‐Hu Chang · 1×
Citations per year

Countries citing papers authored by Long Liu

Since Specialization
Citations

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

Fields of papers citing papers by Long Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
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13 20216
14 20165
15 201614
16 201375
17 2013111
18 2012103
19 2012299
20 20112

About Long Liu

Long Liu is a scholar working on Medical Laboratory Technology, Management Science and Operations Research, Management of Technology and Innovation, Statistics, Probability and Uncertainty and Safety, Risk, Reliability and Quality, having authored 36 papers that have together received 1.9k indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (7 papers), Human-Automation Interaction and Safety (5 papers), Risk and Safety Analysis (4 papers), Quality Function Deployment in Product Design (3 papers), Traffic and Road Safety (3 papers), Transportation and Mobility Innovations (2 papers), Healthcare Operations and Scheduling Optimization (2 papers) and Occupational Health and Safety Research (2 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (722 citations), Management Science and Operations Research (899 citations), Medical Laboratory Technology (72 citations), Management of Technology and Innovation (274 citations) and Safety, Risk, Reliability and Quality (338 citations). Long Liu has collaborated with scholars based in China, Japan and Germany. Frequent co-authors include Hu‐Chen Liu, Nan Liu, Qinglian Lin, Ling‐Xiang Mao, Jing Wu, Ping Li, Na Dong, Pengcheng Xu, Donald Lien and Ping Li. Their work appears in journals such as Expert Systems with Applications, Economics Letters, Geomatics Natural Hazards and Risk, Technology in Cancer Research & Treatment and Humanities and Social Sciences Communications.

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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