Charles M. Macal

8.3k total citations · 3 hit papers
105 papers, 5.2k citations indexed

About

Charles M. Macal is a scholar working on Management Science and Operations Research, Artificial Intelligence and Sociology and Political Science. According to data from OpenAlex, Charles M. Macal has authored 105 papers receiving a total of 5.2k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Management Science and Operations Research, 22 papers in Artificial Intelligence and 13 papers in Sociology and Political Science. Recurrent topics in Charles M. Macal's work include Simulation Techniques and Applications (27 papers), Complex Systems and Decision Making (25 papers) and Multi-Agent Systems and Negotiation (19 papers). Charles M. Macal is often cited by papers focused on Simulation Techniques and Applications (27 papers), Complex Systems and Decision Making (25 papers) and Multi-Agent Systems and Negotiation (19 papers). Charles M. Macal collaborates with scholars based in United States, United Kingdom and Canada. Charles M. Macal's co-authors include Michael North, Jonathan Ozik, Nicholson Collier, Michael North, Mark Bragen, Eric Tatara, Pam Sydelko, Michael Pidd, Peer‐Olaf Siebers and John C. Garnett and has published in prestigious journals such as Nature, PLoS ONE and Energy Policy.

In The Last Decade

Charles M. Macal

103 papers receiving 4.9k citations

Hit Papers

Tutorial on agent-based modelling and simulation 2010 2026 2015 2020 2010 2013 2016 250 500 750 1000

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Charles M. Macal United States 28 1.6k 564 510 494 480 105 5.2k
Theodor J. Stewart South Africa 33 3.0k 1.9× 823 1.5× 336 0.7× 246 0.5× 1.1k 2.2× 113 7.3k
Chung‐Hsing Yeh Australia 36 1.9k 1.2× 683 1.2× 190 0.4× 420 0.9× 247 0.5× 158 5.6k
Rafael Caballero Spain 38 857 0.5× 364 0.6× 608 1.2× 344 0.7× 379 0.8× 166 4.3k
Luís G. Vargas United States 42 4.1k 2.6× 1.0k 1.8× 481 0.9× 279 0.6× 846 1.8× 175 10.6k
George Mavrotas Greece 32 1.6k 1.0× 322 0.6× 162 0.3× 211 0.4× 624 1.3× 74 6.0k
Michael Pidd United Kingdom 29 1.8k 1.1× 418 0.7× 250 0.5× 183 0.4× 500 1.0× 116 4.1k
Valerie Belton United Kingdom 29 3.4k 2.1× 1.1k 1.9× 402 0.8× 171 0.3× 922 1.9× 65 6.7k
Bernard Roy France 38 4.3k 2.8× 1.4k 2.4× 340 0.7× 288 0.6× 787 1.6× 116 8.1k
Hepu Deng Australia 32 1.6k 1.0× 483 0.9× 564 1.1× 147 0.3× 233 0.5× 181 4.7k
Milan Zelený United States 31 2.1k 1.4× 491 0.9× 341 0.7× 156 0.3× 537 1.1× 127 5.2k

Countries citing papers authored by Charles M. Macal

Since Specialization
Citations

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

Fields of papers citing papers by Charles M. Macal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Charles M. Macal. 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 Charles M. Macal. The network helps show where Charles M. Macal may publish in the future.

Co-authorship network of co-authors of Charles M. Macal

This figure shows the co-authorship network connecting the top 25 collaborators of Charles M. Macal. A scholar is included among the top collaborators of Charles M. Macal 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 Charles M. Macal. Charles M. Macal 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
1.
Lindau, Stacy Tessler, Jennifer A. Makelarski, Emily Abramsohn, et al.. (2021). Building and experimenting with an agent-based model to study the population-level impact of CommunityRx, a clinic-based community resource referral intervention. PLoS Computational Biology. 17(10). e1009471–e1009471. 6 indexed citations
2.
Macal, Charles M., et al.. (2018). A generalized agent based framework for modeling a blockchain system. Winter Simulation Conference. 1001–1012. 4 indexed citations
3.
Martinez‐Moyano, Ignacio J. & Charles M. Macal. (2016). A primer for hybrid modeling and simulation. Winter Simulation Conference. 133–147. 2 indexed citations
4.
Cheng, Russell, Charles M. Macal, Barry L. Nelson, et al.. (2016). Simulation: the past 10 years and the next 10 years. Winter Simulation Conference. 2180–2192. 3 indexed citations
5.
Tolk, Andreas, Osman Balcı, C. Donald Combs, et al.. (2015). Do we need a national research agenda for modeling and simulation. Winter Simulation Conference. 2571–2585. 4 indexed citations
6.
North, Michael, John T. Murphy, Pam Sydelko, et al.. (2015). Integrated modeling of conflict and energy. Winter Simulation Conference. 2499–2510. 4 indexed citations
7.
Macal, Charles M., Prakash Thimmapuram, Vladimir Koritarov, et al.. (2014). Agent-based modeling of electric power markets. Winter Simulation Conference. 276–287. 2 indexed citations
8.
Macal, Charles M., Diane Graziano, & Jonathan Ozik. (2014). Modeling Solar PV Adoption: A Social-Behavioral Agent-Based Framework. National Conference on Artificial Intelligence. 11 indexed citations
9.
Martinez‐Moyano, Ignacio J. & Charles M. Macal. (2013). Exploring feedback and endogeneity in agent-based models. Winter Simulation Conference. 1637–1648. 2 indexed citations
10.
Macal, Charles M. & Michael North. (2013). Agent-based modeling and simulation: introductory tutorial. Winter Simulation Conference. 362–376. 6 indexed citations
11.
Macal, Charles M., Michael North, Nicholson Collier, et al.. (2012). Modeling the spread of community-associated MRSA. Winter Simulation Conference. 73. 9 indexed citations
12.
Singh, Ashima, Michael David, Sarah M. Bartsch, et al.. (2012). The economic burden of community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA). Clinical Microbiology and Infection. 19(6). 528–536. 157 indexed citations
13.
Buss, Arnold H., et al.. (2011). Cross-paradigm simulation modeling: challenges and successes. Winter Simulation Conference. 2788–2802. 27 indexed citations
14.
Macal, Charles M. & Michael North. (2010). Toward teaching agent-based simulation. Winter Simulation Conference. 268–277. 20 indexed citations
15.
Macal, Charles M. & Michael North. (2009). Agent-based modeling and simulation. Winter Simulation Conference. 86–98. 195 indexed citations
16.
Macal, Charles M. & Michael North. (2007). Agent-based modeling and simulation: desktop ABMS. Winter Simulation Conference. 95–106. 67 indexed citations
17.
Burke, James, et al.. (2002). Adding the infrastructure class hierarchy to the EXHORT framework for object-oriented deployment simulations.. University of North Texas Digital Library (University of North Texas). 1 indexed citations
18.
Love, Richard, et al.. (2000). The transportation system capability model (TRANSCAP) : a mixed language development approach for an army deployment simulation.. University of North Texas Digital Library (University of North Texas). 2 indexed citations
19.
Burke, James, et al.. (1999). Standardization of transportation classes for object-oriented deployment simulations.. Nature. 216(5115). 613–4. 2 indexed citations
20.
Standridge, Charles R., et al.. (1977). A simulation model of the primary health care system of Indiana. Winter Simulation Conference. 348–358. 8 indexed citations

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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