Ming Ji

54 papers receiving 660 citations

Peers

Ming Ji
Comparison fields: 5 of 107
  • Radiological and Ultrasound Technology 194
  • Statistics, Probability and Uncertainty 136
  • Chemical Health and Safety 9
  • Social Psychology 198
  • Organizational Behavior and Human Resource Management 96
Replace Markus Schöbel with:
Markus Schöbel Germany
Sean Tucker Canada
Nick McDonald Ireland
Yixin Hu China
Timothy D. Ludwig United States
Shezeen Oah South Korea
Daniel Jenkins United States
José Orlando Gomes Brazil
Dongo Rémi Kouabénan France
Ming Ji relative to Markus Schöbel Germany Markus Schöbel's profile →
Citations per field
00.5×7.3×
Markus Schöbel · 1×
Citations per year

Countries citing papers authored by Ming Ji

Since Specialization
Citations

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

Fields of papers citing papers by Ming Ji

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201177
2 201363
3 202458
4 202140
5 202137
6 201934
7 201832
8 202222
9 202020
10 201719
11 200917
12 202316
13 201816
14 201913
15 201312
16 201912
17 202012
18 202111
19 202011
20 202011

About Ming Ji

Ming Ji is a scholar working on Social Psychology, Radiological and Ultrasound Technology, Statistics, Probability and Uncertainty, Clinical Psychology and Organizational Behavior and Human Resource Management, having authored 56 papers that have together received 680 indexed citations. Recurring topics across this work include Occupational Health and Safety Research (15 papers), Risk and Safety Analysis (12 papers), Job Satisfaction and Organizational Behavior (8 papers), Human-Automation Interaction and Safety (5 papers), Ship Hydrodynamics and Maneuverability (4 papers), Advanced Algorithms and Applications (4 papers), Safety Warnings and Signage (4 papers) and Workplace Health and Well-being (3 papers). The work is most often cited by research in Radiological and Ultrasound Technology (194 citations), Statistics, Probability and Uncertainty (136 citations), Chemical Health and Safety (9 citations), Social Psychology (198 citations) and Organizational Behavior and Human Resource Management (96 citations). Ming Ji has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Xuqun You, Jijun Lan, Xuqun You, Lihua Liang, Chia‐Huei Wu, Yuntao Dong, Zhi Liu, Hongwei Li, Bo Liu and Ying Li. Their work appears in journals such as Safety Science, Journal of Air Transport Management, Ocean Engineering, International Journal of Industrial Ergonomics and Academy of Management Journal.

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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