Mark J. Wierman

2.3k citations
45 papers · 1.5k indexed · h-index 12
Topics
Multi-Criteria Decision Making (18 papers)Rough Sets and Fuzzy Logic (11 papers)Fuzzy Logic and Control Systems (5 papers)
Journals
SHILAP Revista de lepidopterologíaInformation SciencesFuzzy Sets and Systems
Partner nations
United StatesChina

In The Last Decade

Mark J. Wierman

39 papers receiving 1.4k citations

Peers

Mark J. Wierman
Comparison fields: 5 of 148
  • Artificial Intelligence 571
  • Management Science and Operations Research 524
  • Computational Theory and Mathematics 493
  • Information Systems 214
  • Statistics, Probability and Uncertainty 137
Replace Alistair Smith with:
Alistair Smith United Kingdom
Joaquín Abellán Spain
Van‐Nam Huynh Japan
Marco Zaffalon Switzerland
Petr Ekel Brazil
Xinyang Deng China
Liguo Fei China
Chonghui Guo China
Marc Pirlot Belgium
Mark J. Wierman relative to Alistair Smith United Kingdom Alistair Smith's profile →
Citations per field
00.5×1.5×1.9×
Alistair Smith · 1×
Citations per year

Countries citing papers authored by Mark J. Wierman

Since Specialization
Citations

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

Fields of papers citing papers by Mark J. Wierman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark J. Wierman. 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 Mark J. Wierman. The network helps show where Mark J. Wierman may publish in the future.

Co-authorship network of co-authors of Mark J. Wierman

This figure shows the co-authorship network connecting the top 25 collaborators of Mark J. Wierman. A scholar is included among the top collaborators of Mark J. Wierman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mark J. Wierman. Mark J. Wierman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 4
2 3
3 1
4 2
5 1
6 1
7
Assessing Team Performance in Information Systems Projects
4
8 2
9 10
10 1
11 171
12 4
13 36
14 31
15
A new measure to analyze student performance using the likert scale
19
16 15
17 15
18 0
19 154
20 3

About Mark J. Wierman

Mark J. Wierman is a scholar working on Management Science and Operations Research, Computational Theory and Mathematics and Artificial Intelligence, having authored 45 papers that have together received 1.5k indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (18 papers), Rough Sets and Fuzzy Logic (11 papers) and Fuzzy Logic and Control Systems (5 papers). The work is most often cited by research in Management Science and Operations Research (524 citations), Computational Theory and Mathematics (493 citations) and Statistics, Probability and Uncertainty (137 citations). Mark J. Wierman has collaborated with scholars based in United States and China. Frequent co-authors include George J. Klir, William J. Tastle, Janusz Kacprzyk, Jiye Liang, Deyu Li, Zhicai Shi, Uldarico Rex Dumdum, Terry D. Clark, John N. Mordeson and Jennifer Larson. Their work appears in journals such as SHILAP Revista de lepidopterología, Information Sciences and Fuzzy Sets and Systems.

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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