Daniel Schunk

57 papers receiving 2.1k citations

Daniel Schunk's Hit Papers

Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences 2019 · 486 citations
4860+2+4Years since publication100200300400

Peers

Daniel Schunk
Comparison fields: 5 of 166
  • General Decision Sciences 289
  • Safety Research 434
  • Applied Psychology 107
  • Cognitive Neuroscience 363
  • Experimental and Cognitive Psychology 210
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Countries citing papers authored by Daniel Schunk

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Schunk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences
Hit paper breakdown →
2019486
2 2012222
3 2010154
4 2009127
5 2009112
6 2004112
7 200894
8 200579
9
Relevance determination in learning vector quantization
200167
10 201855
11 201355
12 201653
13 201552
14 200945
15 200044
16 200843
17 200940
18 201230
19 201630
20 201230

About Daniel Schunk

Daniel Schunk is a scholar working on Safety Research, General Decision Sciences, Economics and Econometrics, Management Science and Operations Research and Demography, having authored 60 papers that have together received 2.3k indexed citations. Recurring topics across this work include Experimental Behavioral Economics Studies (17 papers), Decision-Making and Behavioral Economics (12 papers), Economic and Environmental Valuation (9 papers), Psychology of Moral and Emotional Judgment (6 papers), Genetic Associations and Epidemiology (5 papers), Cognitive Abilities and Testing (4 papers), Financial Literacy, Pension, Retirement Analysis (4 papers) and Gender, Labor, and Family Dynamics (4 papers). The work is most often cited by research in General Decision Sciences (289 citations), Safety Research (434 citations), Applied Psychology (107 citations), Cognitive Neuroscience (363 citations) and Experimental and Cognitive Psychology (210 citations). Daniel Schunk has collaborated with scholars based in Germany, Switzerland and United States. Frequent co-authors include Ernst Fehr, Joachim Winter, Daniel E. Houser, Adrian Bruhin, Brian M. Deal, Björn Bartling, Christian Carl Ruff, Yosuke Morishima, Cornelia Betsch and Michel André Maréchal. Their work appears in journals such as Journal of Economic Behavior & Organization, Journal of Economic Psychology, Experimental Economics, Journal of Behavioral and Experimental Economics and Journal of the European Economic Association.

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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