János Mayer

1.2k citations
25 papers · 463 · h-index 10

Impact in

Papers in

János Mayer

21 papers receiving 422 citations

Peers

János Mayer
Comparison fields: 5 of 76
  • General Decision Sciences 49
  • Management Science and Operations Research 261
  • Finance 109
  • Statistics and Probability 56
  • Control and Systems Engineering 145
Replace Csaba I. Fábián with:
Csaba I. Fábián Hungary
Jianjun Gao China
Pavlo A. Krokhmal United States
William B. Haskell United States
Martin Branda Czechia
Gábor Rudolf United States
Manfred Schäl Germany
Ralph E. Strauch United States
Zhaolin Hu China
Churlzu Lim United States
János Mayer relative to Csaba I. Fábián Hungary Csaba I. Fábián's profile →
Citations per field
00.5×3.8×
Csaba I. Fábián · 1×
Citations per year

Countries citing papers authored by János Mayer

Since Specialization
Citations

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

Fields of papers citing papers by János Mayer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside János Mayer, 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 János Mayer Line = papers co-authored together János Mayer links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010219
2 200573
3 199625
4 200425
5 200724
6 198917
7 201415
8
Stochastic Linear Programming Algorithms: A Comparison Based on a Model Management System
199814
9 201011
10 200810
11 20176
12 20066
13 19944
14 19923
15 20143
16 20222
17 20172
18 20131
19 20121
20 20101

About János Mayer

János Mayer is a scholar working on Management Science and Operations Research, Finance, Economics and Econometrics, General Decision Sciences and Numerical Analysis, having authored 25 papers that have together received 463 indexed citations. Recurring topics across this work include Risk and Portfolio Optimization (12 papers), Financial Markets and Investment Strategies (6 papers), Decision-Making and Behavioral Economics (6 papers), Stochastic processes and financial applications (3 papers), Insurance, Mortality, Demography, Risk Management (3 papers), Economic theories and models (3 papers), Advanced Optimization Algorithms Research (3 papers) and Insurance and Financial Risk Management (3 papers). The work is most often cited by research in General Decision Sciences (49 citations), Management Science and Operations Research (261 citations), Finance (109 citations), Statistics and Probability (56 citations) and Control and Systems Engineering (145 citations). János Mayer has collaborated with scholars based in Switzerland, Norway and China. Frequent co-authors include Peter Kall, Thorsten Hens, Enrico De Giorgi, Tamás Terlaky, Enrico G. De Giorgi, Tibor Illés, András Prékopa, István Deák, P. Kall and Karl Schmedders. Their work appears in journals such as European Journal of Operational Research, Engineering Optimization, Computational Economics, Optimization and Annals of Operations Research.

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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