Wanting Wu

37 papers receiving 514 citations

Wanting Wu's Hit Papers

Fintech inputs, non-performing loans risk reduction and bank performance improvement 2023 · 80 citations
800+1+2Years since publication255075

Peers

Wanting Wu
Comparison fields: 5 of 129
  • Management Information Systems 63
  • Accounting 76
  • Finance 64
  • Reproductive Medicine 41
  • Transportation 24
Replace Sungmook Lim with:
Sungmook Lim South Korea
Kristina Šutienė Lithuania
Mohammed Umar Nigeria
Erwin M. Saniga United States
Kevin McNally United Kingdom
Alejandro Peña Colombia
Ronald K. Klimberg United States
I. M. Premachandra New Zealand
Wanting Wu relative to Sungmook Lim South Korea Sungmook Lim's profile →
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Citations per year

Countries citing papers authored by Wanting Wu

Since Specialization
Citations

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

Fields of papers citing papers by Wanting Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Fintech inputs, non-performing loans risk reduction and bank performance improvement
Hit paper breakdown →
202380
2 202172
3 202246
4 201932
5 201430
6 202426
7
APPLYING ANALYTIC NETWORK PROCESS IN LOGISTICS SERVICE PROVIDER SELECTION - A CASE STUDY OF THE INDUSTRY INVESTING IN SOUTHEAST ASIA
201120
8 202220
9 201819
10 201819
11 201416
12 201615
13 202213
14 201711
15 202010
16 202110
17 202010
18 20168
19 20257
20 20247

About Wanting Wu

Wanting Wu is a scholar working on Public Health, Environmental and Occupational Health, Molecular Biology, Computational Theory and Mathematics, Cardiology and Cardiovascular Medicine and Complementary and alternative medicine, having authored 40 papers that have together received 536 indexed citations. Recurring topics across this work include Malaria Research and Control (8 papers), Mosquito-borne diseases and control (6 papers), Computational Drug Discovery Methods (5 papers), Ovarian function and disorders (3 papers), Microfinance and Financial Inclusion (3 papers), Moringa oleifera research and applications (3 papers), Healthcare and Venom Research (2 papers) and Corporate Finance and Governance (2 papers). The work is most often cited by research in Management Information Systems (63 citations), Accounting (76 citations), Finance (64 citations), Reproductive Medicine (41 citations) and Transportation (24 citations). Wanting Wu has collaborated with scholars based in China, Taiwan and United States. Frequent co-authors include Haijun Wang, Haohan Luo, Yuchao Peng, Liqun Peng, Tuqiang Zhou, Zhixiong Li, Kai-Ying Chen, Mingyang Zhang, Ming‐Chang Wu and Maohua Lai. Their work appears in journals such as Frontiers in Pharmacology, Industrial Crops and Products, International Review of Financial Analysis, Acta Psychologica and Scientific Reports.

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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