Eric Wang

20 papers receiving 306 citations

Peers

Eric Wang
Comparison fields: 5 of 74
  • Computer Science Applications 39
  • Accounting 68
  • General Social Sciences 9
  • Artificial Intelligence 84
  • Strategy and Management 37
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Namhyoung Kim South Korea
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Countries citing papers authored by Eric Wang

Since Specialization
Citations

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

Fields of papers citing papers by Eric Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201462
2 200755
3 200533
4 202432
5 200929
6 202426
7 200821
8
Stochastic Optimization of Sorting Networks via Continuous Relaxations
201910
9 201210
10
Dynamics of canadian oil price and its impact on exchange rate and stock market
20189
11 20139
12 20198
13
Service Function Chaining Use Cases for Network Security
20177
14 20224
15
Value – Function – Structure Modeling in an Ontological Representation of Product-Service Systems
20093
16 20092
17 20182
18 20112
19
An Empirical Analysis of Canadian Shareholder Proposals
20071
20 20071

About Eric Wang

Eric Wang is a scholar working on Artificial Intelligence, Information Systems, Accounting, Finance and Computer Science Applications, having authored 23 papers that have together received 326 indexed citations. Recurring topics across this work include Corporate Finance and Governance (6 papers), Bayesian Methods and Mixture Models (4 papers), Online Learning and Analytics (3 papers), Auditing, Earnings Management, Governance (3 papers), Private Equity and Venture Capital (3 papers), Financial Markets and Investment Strategies (2 papers), Blockchain Technology Applications and Security (2 papers) and Cryptography and Data Security (2 papers). The work is most often cited by research in Computer Science Applications (39 citations), Accounting (68 citations), General Social Sciences (9 citations), Artificial Intelligence (84 citations) and Strategy and Management (37 citations). Eric Wang has collaborated with scholars based in Canada, United States and China. Frequent co-authors include Shamsud D. Chowdhury, Lawrence Carin, Jay Brockman, Adam Carberry, Ben Rydal Shapiro, Chris Rogers, Hu Xiong, David B. Dunson, Chih‐Ping Chou and Mary Ann Pentz. Their work appears in journals such as IEEE Transactions on Consumer Electronics, Evaluation and Program Planning, International Journal of Energy Economics and Policy, Journal of Management & Governance and IEEE Transactions on Pattern Analysis and Machine Intelligence.

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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