Ming-Fu Hsu

644 citations
27 papers · 467 · h-index 10

Impact in

Papers in

Ming-Fu Hsu

27 papers receiving 438 citations

Peers

Ming-Fu Hsu
Comparison fields: 5 of 68
  • Accounting 237
  • Management Science and Operations Research 143
  • Artificial Intelligence 255
  • Management Information Systems 49
  • Finance 50
Replace Chun‐Ling Chuang with:
Chun‐Ling Chuang Taiwan
Rua‐Huan Tsaih Taiwan
Rashmi Malhotra United States
Efstathios Kirkos Greece
Markku Heikkilä Finland
Linda Salchenberger United States
Yakup Selvı Türkiye
Ana I. Marqués Spain
Maumita Bhattacharya Australia
P. Ravisankar India
Ming-Fu Hsu relative to Chun‐Ling Chuang Taiwan Chun‐Ling Chuang's profile →
Citations per field
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Chun‐Ling Chuang · 1×
Citations per year

Countries citing papers authored by Ming-Fu Hsu

Since Specialization
Citations

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

Fields of papers citing papers by Ming-Fu Hsu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 14 scholars most cited alongside Ming-Fu Hsu, 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-Fu Hsu Line = papers co-authored together Ming-Fu Hsu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009133
2 201089
3 201247
4 201246
5 201329
6 202323
7 201512
8 202112
9 201611
10 20229
11 20219
12
Knowledge Based Consultation for Finite Element Structural Analysis.
19808
13 20235
14 20095
15 20145
16 20154
17 20233
18 20133
19 20233
20 20242

About Ming-Fu Hsu

Ming-Fu Hsu is a scholar working on Accounting, Artificial Intelligence, Management Science and Operations Research, Management Information Systems and Computational Theory and Mathematics, having authored 27 papers that have together received 467 indexed citations. Recurring topics across this work include Financial Distress and Bankruptcy Prediction (16 papers), Imbalanced Data Classification Techniques (13 papers), Stock Market Forecasting Methods (7 papers), Rough Sets and Fuzzy Logic (6 papers), Efficiency Analysis Using DEA (4 papers), Big Data and Business Intelligence (3 papers), Forecasting Techniques and Applications (2 papers) and Supply Chain Resilience and Risk Management (2 papers). The work is most often cited by research in Accounting (237 citations), Management Science and Operations Research (143 citations), Artificial Intelligence (255 citations), Management Information Systems (49 citations) and Finance (50 citations). Ming-Fu Hsu has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include Der‐Jang Chi, Ching-Chiang Yeh, Ping‐Feng Pai, Sin‐Jin Lin, Fu-Hsiang Chen, Te-Min Chang, Jui‐Jung Liao, Gwo‐Hshiung Tzeng, Jhih‐Hong Zeng and Pedro V. Marcal. Their work appears in journals such as Knowledge-Based Systems, Journal of Global Information Management, Research in International Business and Finance, International Journal of Machine Learning and Cybernetics and Global economy 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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