The Jin Ai

831 total citations
30 papers, 615 citations indexed

About

The Jin Ai is a scholar working on Industrial and Manufacturing Engineering, Management Information Systems and Building and Construction. According to data from OpenAlex, The Jin Ai has authored 30 papers receiving a total of 615 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Industrial and Manufacturing Engineering, 12 papers in Management Information Systems and 6 papers in Building and Construction. Recurrent topics in The Jin Ai's work include Supply Chain and Inventory Management (9 papers), Vehicle Routing Optimization Methods (6 papers) and Scheduling and Optimization Algorithms (5 papers). The Jin Ai is often cited by papers focused on Supply Chain and Inventory Management (9 papers), Vehicle Routing Optimization Methods (6 papers) and Scheduling and Optimization Algorithms (5 papers). The Jin Ai collaborates with scholars based in Indonesia, Thailand and Taiwan. The Jin Ai's co-authors include Voratas Kachitvichyanukul, T.M.A. Ari Samadhi, Hui‐Ming Wee, Huang Hu, Huynh Trung Luong, Lida Huang, Dah-Chuan Gong, Feng Jiao, Rencheng Song and Paulus Wisnu Anggoro and has published in prestigious journals such as Computers & Operations Research, Computers & Industrial Engineering and The TQM Journal.

In The Last Decade

The Jin Ai

27 papers receiving 578 citations

Peers

The Jin Ai
Comparison fields: 5 of 57
  • Industrial and Manufacturing Engineering 470
  • Automotive Engineering 180
  • Building and Construction 143
  • Artificial Intelligence 136
  • Strategy and Management 49
Replace Michel Toulouse with:
Michel Toulouse Canada
Daniele Ferone Italy
Francisco Ángel-Bello Mexico
İmdat Kara Türkiye
Emanuela Guerriero Italy
Giuseppe Paletta Italy
Diana G. Ramirez-Ríos United States
Paweł Sitek Poland
Nicola Bianchessi Italy
Michel Toulouse Canada View profile →
Citations per field, relative to The Jin Ai
The Jin Ai · 1×
Citations per year, relative to The Jin Ai
The Jin Ai · 1×

Countries citing papers authored by The Jin Ai

Since Specialization
Citations

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

Fields of papers citing papers by The Jin Ai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of The Jin Ai

This figure shows the co-authorship network connecting the top 25 collaborators of The Jin Ai. A scholar is included among the top collaborators of The Jin Ai based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with The Jin Ai. The Jin Ai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 1
3 2
4 7
5 1
6 1
7 3
8 4
9 0
10 2
11 19
12 1
13 4
14 1
15 1
16 1
17 36
18 156
19 319
20 11

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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