Daniel M. Bartels

2.1k total citations
56 papers, 1.0k citations indexed

About

Daniel M. Bartels is a scholar working on General Decision Sciences, Social Psychology and Cognitive Neuroscience. According to data from OpenAlex, Daniel M. Bartels has authored 56 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in General Decision Sciences, 18 papers in Social Psychology and 17 papers in Cognitive Neuroscience. Recurrent topics in Daniel M. Bartels's work include Decision-Making and Behavioral Economics (21 papers), Psychology of Moral and Emotional Judgment (16 papers) and Psychological Well-being and Life Satisfaction (8 papers). Daniel M. Bartels is often cited by papers focused on Decision-Making and Behavioral Economics (21 papers), Psychology of Moral and Emotional Judgment (16 papers) and Psychological Well-being and Life Satisfaction (8 papers). Daniel M. Bartels collaborates with scholars based in United States, Netherlands and Australia. Daniel M. Bartels's co-authors include Oleg Urminsky, Douglas L. Medin, Berkeley J. Dietvorst, Jeffrey R. Parker, Christoph Ungemach, Neil Stewart, Ben R. Newell, Adam J. L. Harris, Gabriele Paolacci and Jesse Chandler and has published in prestigious journals such as Journal of Personality and Social Psychology, Trends in Cognitive Sciences and Journal of Marketing Research.

In The Last Decade

Daniel M. Bartels

55 papers receiving 933 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel M. Bartels United States 18 322 289 267 206 158 56 1.0k
Katherine A. Burson United States 11 265 0.8× 158 0.5× 171 0.6× 259 1.3× 194 1.2× 25 981
Jonathan Z. Berman United States 12 497 1.5× 288 1.0× 259 1.0× 64 0.3× 176 1.1× 24 941
Oleg Urminsky United States 14 341 1.1× 103 0.4× 222 0.8× 246 1.2× 360 2.3× 55 1.1k
Irene Scopelliti United Kingdom 10 183 0.6× 119 0.4× 158 0.6× 126 0.6× 153 1.0× 26 724
Evan Polman United States 19 564 1.8× 316 1.1× 464 1.7× 355 1.7× 313 2.0× 46 1.6k
Nicola J. Bown United Kingdom 11 517 1.6× 177 0.6× 341 1.3× 114 0.6× 68 0.4× 15 1.1k
Hans‐Peter Erb Germany 20 801 2.5× 152 0.5× 469 1.8× 101 0.5× 155 1.0× 45 1.3k
Tom Meyvis United States 16 571 1.8× 249 0.9× 364 1.4× 159 0.8× 788 5.0× 45 1.6k
Rachel Barkan Israel 16 384 1.2× 397 1.4× 224 0.8× 221 1.1× 54 0.3× 22 1.0k
Selin A. Malkoc United States 16 235 0.7× 134 0.5× 261 1.0× 469 2.3× 385 2.4× 34 1.2k

Countries citing papers authored by Daniel M. Bartels

Since Specialization
Citations

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

Fields of papers citing papers by Daniel M. Bartels

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel M. Bartels

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel M. Bartels. A scholar is included among the top collaborators of Daniel M. Bartels 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 Daniel M. Bartels. Daniel M. Bartels 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.
Aka, Ada, Daniel M. Bartels, Stefan Bucher, et al.. (2025). A timeline of cognitive costs in decision-making. Trends in Cognitive Sciences. 29(9). 827–839. 2 indexed citations
2.
Bartels, Daniel M., et al.. (2023). How well do laboratory-derived estimates of time preference predict real-world behaviors? Comparisons to four benchmarks.. Journal of Experimental Psychology General. 152(9). 2651–2665. 5 indexed citations
3.
Bartels, Daniel M., et al.. (2017). A Longitudinal Study of Differences between Predicted, Actual, and Remembered Personal Change.. Cognitive Science. 1 indexed citations
4.
Bartels, Daniel M. & Abigail B. Sussman. (2017). Anchors Or Targets? An Examination of Credit Card Statements. ACR North American Advances. 2 indexed citations
5.
Landy, Justin F., et al.. (2017). What’s wrong with using steroids? Exploring whether and why people oppose the use of performance enhancing drugs.. Journal of Personality and Social Psychology. 113(3). 377–392. 10 indexed citations
6.
Bartels, Daniel M., et al.. (2015). On the Mental Accounting of Restricted-Use Funds: How Gift Cards Change What People Purchase. SSRN Electronic Journal. 30 indexed citations
7.
Bartels, Daniel M., et al.. (2015). Personal Change and the Continuity of Identity.. Cognitive Science. 2 indexed citations
8.
Stewart, Neil, Christoph Ungemach, Adam J. L. Harris, et al.. (2015). The average laboratory samples a population of 7,300 Amazon Mechanical Turk workers. Judgment and Decision Making. 10(5). 479–491. 167 indexed citations
9.
Bartels, Daniel M. & Oleg Urminsky. (2014). To Know and to Care: How Awareness and Valuation of the Future Jointly Shape Consumer Spending. SSRN Electronic Journal. 1 indexed citations
10.
Bartels, Daniel M., et al.. (2014). How Awareness and Valuation of the Future Jointly Shape Intertemporal Financial Decisions. Cognitive Science. 36(36). 1 indexed citations
11.
Bartels, Daniel M. & Eric J. Johnson. (2014). Connecting cognition and consumer choice. Cognition. 135. 47–51. 37 indexed citations
12.
Robinson, Paul H., et al.. (2012). Extralegal Punishment Factors: A Study of Forgiveness, Hardship, Good-Deeds, Apology, Remorse, and Other Such Discretionary Factors in Assessing Criminal Punishment. Vanderbilt law review. 65(3). 735. 5 indexed citations
13.
Caruso, Eugene M., et al.. (2011). Predicting premeditation: Future behavior is seen as more intentional than past behavior.. Journal of Experimental Psychology General. 141(2). 227–232. 26 indexed citations
14.
Bartels, Daniel M. & David A. Pizarro. (2011). The mismeasure of morals: Antisocial personality traits predict utilitarian responses to moral dilemmas. Cognition. 121(1). 154–161. 22 indexed citations
15.
Medin, Douglas L., et al.. (2010). Perspectives on the Ecology of Decision Modes: Reply to Comments. SSRN Electronic Journal. 1 indexed citations
16.
Iliev, Rumen, Sonya Sachdeva, Daniel M. Bartels, et al.. (2009). Attending to moral values. SSRN Electronic Journal. 11 indexed citations
17.
Bartels, Daniel M.. (2008). Principled moral sentiment and the flexibility of moral judgment and decision making. Cognition. 108(2). 381–417. 8 indexed citations
18.
Bartels, Daniel M. & Samuel B. Day. (2006). Representation Across Time: Generalizing Temporal Effects on Perceived Similarity. eScholarship (California Digital Library). 28(28). 1 indexed citations
19.
Bartels, Daniel M. & Samuel B. Day. (2005). The Effects of Prior Use on Preference. eScholarship (California Digital Library). 27(27). 3 indexed citations
20.
Day, Samuel B. & Daniel M. Bartels. (2004). Temporal Distance, Event Representation, and Similarity. eScholarship (California Digital Library). 26(26). 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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