Murali Shanker

922 total citations
32 papers, 638 citations indexed

About

Murali Shanker is a scholar working on Management Science and Operations Research, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Murali Shanker has authored 32 papers receiving a total of 638 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Management Science and Operations Research, 6 papers in Artificial Intelligence and 5 papers in Computer Networks and Communications. Recurrent topics in Murali Shanker's work include Simulation Techniques and Applications (9 papers), Distributed and Parallel Computing Systems (5 papers) and Neural Networks and Applications (5 papers). Murali Shanker is often cited by papers focused on Simulation Techniques and Applications (9 papers), Distributed and Parallel Computing Systems (5 papers) and Neural Networks and Applications (5 papers). Murali Shanker collaborates with scholars based in United States, Hong Kong and Australia. Murali Shanker's co-authors include Michael Y. Hu, Ming S. Hung, Ikpe Justice Akpan, Marvin D. Troutt, Jing Wang, Kholekile L. Gwebu, Kevin J. Trainor, Rouzbeh Razavi, B. Eddy Patuwo and Jing Wang and has published in prestigious journals such as European Journal of Operational Research, Journal of Business Research and International Journal of Production Economics.

In The Last Decade

Murali Shanker

30 papers receiving 602 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Murali Shanker United States 12 128 116 60 58 49 32 638
Stefanka Chukova New Zealand 19 107 0.8× 132 1.1× 39 0.7× 129 2.2× 112 2.3× 90 1.2k
Simona Dziţac Romania 15 209 1.6× 109 0.9× 72 1.2× 64 1.1× 34 0.7× 57 913
Anil Jadhav India 8 115 0.9× 176 1.5× 31 0.5× 26 0.4× 85 1.7× 25 691
Azlinah Mohamed Malaysia 16 75 0.6× 305 2.6× 81 1.4× 43 0.7× 157 3.2× 109 1.2k
Indranil Bose India 8 148 1.2× 460 4.0× 54 0.9× 40 0.7× 40 0.8× 21 824
Daniel T. Larose United States 10 58 0.5× 358 3.1× 42 0.7× 24 0.4× 42 0.9× 14 1.2k
Hojjat Adeli United States 12 96 0.8× 140 1.2× 30 0.5× 33 0.6× 28 0.6× 30 645
Wanru Wang China 11 83 0.6× 118 1.0× 45 0.8× 89 1.5× 63 1.3× 27 709
Omed Hassan Ahmed Iraq 18 53 0.4× 158 1.4× 63 1.1× 45 0.8× 42 0.9× 39 838
Lila Rajabion United States 16 33 0.3× 99 0.9× 46 0.8× 107 1.8× 81 1.7× 34 764

Countries citing papers authored by Murali Shanker

Since Specialization
Citations

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

Fields of papers citing papers by Murali Shanker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Murali Shanker

This figure shows the co-authorship network connecting the top 25 collaborators of Murali Shanker. A scholar is included among the top collaborators of Murali Shanker 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 Murali Shanker. Murali Shanker 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.
Akpan, Ikpe Justice, Murali Shanker, & O. Felix Offodile. (2023). Discrete‐event simulation is still alive and strong: evidence from bibliometric performance evaluation of research during COVID‐19 global health pandemic. International Transactions in Operational Research. 31(4). 2069–2092. 5 indexed citations
2.
Guiffrida, Alfred L., et al.. (2021). A Generalized Stochastic Cost–Volume–Profit Model. Systems. 9(4). 81–81. 1 indexed citations
3.
Akpan, Ikpe Justice, et al.. (2021). Association Between What People Learned About COVID-19 Using Web Searches and Their Behavior Toward Public Health Guidelines: Empirical Infodemiology Study. Journal of Medical Internet Research. 23(9). e28975–e28975. 23 indexed citations
4.
Akpan, Ikpe Justice, Murali Shanker, & Rouzbeh Razavi. (2019). Improving the success of simulation projects using 3D visualization and virtual reality. Journal of the Operational Research Society. 71(12). 1900–1926. 20 indexed citations
5.
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7.
Shanker, Murali, et al.. (2015). Late customization strategy with service levels requirements. International Journal of Production Economics. 166. 72–84. 6 indexed citations
8.
Datta, Pratim, et al.. (2009). The Marginal Utility of Medical Resources in Clinics with Deterministic Patient Arrivals: A Simulation Study. Journal of the Association for Information Systems. 497.
9.
Wang, Jing, Kholekile L. Gwebu, Murali Shanker, & Marvin D. Troutt. (2008). An application of agent-based simulation to knowledge sharing. Decision Support Systems. 46(2). 532–541. 68 indexed citations
10.
Hu, Michael Y., Murali Shanker, G. Peter Zhang, & Ming S. Hung. (2007). Modeling consumer situational choice of long distance communication with neural networks. Decision Support Systems. 44(4). 899–908. 15 indexed citations
11.
Shanker, Murali & Michael Y. Hu. (2006). A Framework for Distance Education Effectiveness. International Journal of Web-Based Learning and Teaching Technologies. 1(2). 1–17. 1 indexed citations
12.
Troutt, Marvin D., Michael Y. Hu, & Murali Shanker. (2004). A distribution-free approach to estimating best response values with application to mutual fund performance modeling. European Journal of Operational Research. 166(2). 520–527. 3 indexed citations
13.
Shanker, Murali, et al.. (2001). Efficient distributed simulation through dynamic load balancing. IIE Transactions. 33(3). 203–217. 1 indexed citations
14.
Shanker, Murali, Michael Y. Hu, & Ming S. Hung. (2000). Estimating Probabilities of Diabetes Mellitus Using Neural Networks. SAR and QSAR in environmental research. 11(2). 133–147. 6 indexed citations
15.
Shanker, Murali. (1996). Using Neural Networks To Predict the Onset of Diabetes Mellitus. Journal of Chemical Information and Computer Sciences. 36(1). 35–41. 45 indexed citations
16.
Shanker, Murali, Michael Y. Hu, & Ming S. Hung. (1996). Effect of data standardization on neural network training. Omega. 24(4). 385–397. 225 indexed citations
17.
Shanker, Murali, et al.. (1993). Measuring Congestion for Dynamic Task Allocation in Distributed Simulation. INFORMS Journal on Computing. 5(1). 54–68. 2 indexed citations
18.
Shanker, Murali & B. Eddy Patuwo. (1993). The effect of synchronization requirements on the performance of distributed simulations. ACM SIGSIM Simulation Digest. 23(1). 151–154. 2 indexed citations
19.
Hill, Arthur V., Salvatore T. March, Christopher J. Nachtsheim, & Murali Shanker. (1992). An Approximate Model for Field Service Territory Planning. IIE Transactions. 24(1). 2–10. 9 indexed citations
20.
Shanker, Murali, et al.. (1989). Adaptive distribution of model components via congestion measures. 640–647. 2 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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