Michael D. Shields

157 papers receiving 5.7k citations

Michael D. Shields's Hit Papers

The generalization of Latin hypercube sampling 2015 · 401 citations
4010+3+7Years since publication100200300400

Peers

Michael D. Shields
Comparison fields: 5 of 165
  • Management Information Systems 2.4k
  • Accounting 2.2k
  • Statistics, Probability and Uncertainty 1.1k
  • General Decision Sciences 243
  • Strategy and Management 1.1k
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Michael D. Shields relative to Malcolm Smith United Kingdom Malcolm Smith's profile →
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Countries citing papers authored by Michael D. Shields

Since Specialization
Citations

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

Fields of papers citing papers by Michael D. Shields

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael D. Shields. 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 Michael D. Shields. The network helps show where Michael D. Shields may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 164 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003495
2
The generalization of Latin hypercube sampling
Hit paper breakdown →
2015401
3 1999382
4 1998374
5
Research in management accounting by North Americans in the 1990s
1997322
6 2003277
7 1999214
8 2011135
9 2000126
10 1991118
11 1994117
12 2021107
13 200194
14 201590
15 198485
16 199884
17 200277
18 200777
19 201576
20 202272

About Michael D. Shields

Michael D. Shields is a scholar working on Statistics, Probability and Uncertainty, Management Information Systems, Accounting, Statistical and Nonlinear Physics and Civil and Structural Engineering, having authored 164 papers that have together received 6.3k indexed citations. Recurring topics across this work include Probabilistic and Robust Engineering Design (61 papers), Accounting and Organizational Management (38 papers), Auditing, Earnings Management, Governance (29 papers), Model Reduction and Neural Networks (23 papers), Structural Health Monitoring Techniques (18 papers), Advanced Multi-Objective Optimization Algorithms (17 papers), Decision-Making and Behavioral Economics (15 papers) and Experimental Behavioral Economics Studies (13 papers). The work is most often cited by research in Management Information Systems (2.4k citations), Accounting (2.2k citations), Statistics, Probability and Uncertainty (1.1k citations), General Decision Sciences (243 citations) and Strategy and Management (1.1k citations). Michael D. Shields has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Joan L. Luft, Jiaxin Zhang, Jeffrey F. Shields, Chee W. Chow, Ira Solomon, O. Ray Whittington, George Deodatis, Jacob G. Birnberg, Yutaka Kato and Dimitris G. Giovanis. Their work appears in journals such as Accounting Organizations and Society, Probabilistic Engineering Mechanics, Computer Methods in Applied Mechanics and Engineering, Reliability Engineering & System Safety and Journal of Computational Physics.

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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