Hung-da Wan

599 citations
24 papers · 419 · h-index 12

Impact in

Papers in

Hung-da Wan

21 papers receiving 390 citations

Peers

Hung-da Wan
Comparison fields: 5 of 72
  • Management Information Systems 170
  • Industrial and Manufacturing Engineering 169
  • Medical Laboratory Technology 13
  • Strategy and Management 141
  • Management Science and Operations Research 77
Replace Abdellah Abouabdellah with:
Abdellah Abouabdellah Morocco
Alessandro Pozzetti Italy
Claire Palmer United Kingdom
Jan-Philipp Prote Germany
Gregor von Cieminski Germany
Syed Imran Shafiq Australia
Thomas Lundholm Sweden
Nikola Suzić Italy
Sara Antomarioni Italy
James B. Porter United States
Hung-da Wan relative to Abdellah Abouabdellah Morocco Abdellah Abouabdellah's profile →
Citations per field
00.5×1.5×2.5×
Abdellah Abouabdellah · 1×
Citations per year

Countries citing papers authored by Hung-da Wan

Since Specialization
Citations

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

Fields of papers citing papers by Hung-da Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hung-da Wan. 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 Hung-da Wan. The network helps show where Hung-da Wan may publish in the future.

Co-authors

The 20 scholars most cited alongside Hung-da Wan, 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 Hung-da Wan Line = papers co-authored together Hung-da Wan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200972
2 201250
3 200948
4 201231
5 201929
6 201829
7 201829
8 201825
9 201518
10 201917
11 200717
12 201016
13 201110
14 20098
15 20185
16 20205
17 20203
18 20203
19 20241
20 20201

About Hung-da Wan

Hung-da Wan is a scholar working on Industrial and Manufacturing Engineering, Management Information Systems, Management Science and Operations Research, Information Systems and Control and Systems Engineering, having authored 24 papers that have together received 419 indexed citations. Recurring topics across this work include Quality and Supply Management (6 papers), Digital Transformation in Industry (5 papers), Manufacturing Process and Optimization (4 papers), Information and Cyber Security (4 papers), Smart Grid Security and Resilience (4 papers), Operations Management Techniques (3 papers), Big Data and Business Intelligence (2 papers) and Quality and Management Systems (2 papers). The work is most often cited by research in Management Information Systems (170 citations), Industrial and Manufacturing Engineering (169 citations), Medical Laboratory Technology (13 citations), Strategy and Management (141 citations) and Management Science and Operations Research (77 citations). Hung-da Wan has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include F. Frank Chen, Can Saygin, Sanjay Kumar Shukla, Manoj Kumar Tiwari, Ravi Shankar, Shanshan Wu, Beizhi Li, Leonardo Rivera, F. Frank Chen and Li Nie. Their work appears in journals such as Robotics and Computer-Integrated Manufacturing, Computers & Industrial Engineering, Expert Systems with Applications, Journal of Biomechanical Engineering and Computers in Industry.

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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