Jennifer M. Logg

1.9k total citations · 1 hit paper
17 papers, 1.2k citations indexed

About

Jennifer M. Logg is a scholar working on Safety Research, General Decision Sciences and Sociology and Political Science. According to data from OpenAlex, Jennifer M. Logg has authored 17 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Safety Research, 6 papers in General Decision Sciences and 4 papers in Sociology and Political Science. Recurrent topics in Jennifer M. Logg's work include Decision-Making and Behavioral Economics (6 papers), Ethics and Social Impacts of AI (5 papers) and Experimental Behavioral Economics Studies (3 papers). Jennifer M. Logg is often cited by papers focused on Decision-Making and Behavioral Economics (6 papers), Ethics and Social Impacts of AI (5 papers) and Experimental Behavioral Economics Studies (3 papers). Jennifer M. Logg collaborates with scholars based in United States, Canada and Israel. Jennifer M. Logg's co-authors include Don A. Moore, Julia A. Minson, Elizabeth R. Tenney, Charles Dorison, Uriel Haran, Francesca Gino, Leslie K. John, Alison Wood Brooks, Jianmin Sun and Sébastien Brion and has published in prestigious journals such as Journal of Personality and Social Psychology, Journal of Experimental Psychology General and Organizational Behavior and Human Decision Processes.

In The Last Decade

Jennifer M. Logg

15 papers receiving 1.1k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Algorithm appreciation: People prefer algorithmic to human judgment

2019 883 citations Jennifer M. Logg, Julia A. Minson et al. Organizational Behavior and Human Decision Processes profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jennifer M. Logg United States	9	467	334	324	200	194	17	1.2k
Noah Castelo Canada	13	395 0.8×	415 1.2×	500 1.5×	268 1.3×	259 1.3×	24	1.3k
Chiara Longoni United States	10	507 1.1×	662 2.0×	785 2.4×	356 1.8×	294 1.5×	19	1.9k
Andrea Bonezzi United States	13	374 0.8×	922 2.8×	508 1.6×	293 1.5×	406 2.1×	25	2.1k
Michael Yeomans United States	11	157 0.3×	270 0.8×	233 0.7×	85 0.4×	155 0.8×	26	845
Nils Köbis Germany	15	353 0.8×	454 1.4×	109 0.3×	266 1.3×	130 0.7×	39	892
Sarah Bankins Australia	16	227 0.5×	241 0.7×	164 0.5×	59 0.3×	129 0.7×	34	1.1k
Sudeep Bhatia United States	22	141 0.3×	292 0.9×	212 0.7×	270 1.4×	156 0.8×	88	1.3k
Paul Formosa Australia	16	248 0.5×	261 0.8×	186 0.6×	178 0.9×	88 0.5×	67	951
William M. Goldstein United States	14	174 0.4×	204 0.6×	196 0.6×	161 0.8×	133 0.7×	19	1.2k
Andrea L. Guzman United States	11	324 0.7×	454 1.4×	425 1.3×	86 0.4×	190 1.0×	21	1.2k

Countries citing papers authored by Jennifer M. Logg

Since Specialization

Citations

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

Fields of papers citing papers by Jennifer M. Logg

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jennifer M. Logg

This figure shows the co-authorship network connecting the top 25 collaborators of Jennifer M. Logg. A scholar is included among the top collaborators of Jennifer M. Logg 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 Jennifer M. Logg. Jennifer M. Logg is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

Logg, Jennifer M., et al.. (2024). A Simple Explanation Reconciles “Algorithm Aversion” and “Algorithm Appreciation”: Hypotheticals vs. Real Judgments. SSRN Electronic Journal. 2 indexed citations

Logg, Jennifer M., et al.. (2022). Building a Better World Together: Understanding the Future of Work with Algorithms, AI, & Automation. Academy of Management Proceedings. 2022(1). 2 indexed citations

Danks, David, Craig R. Fox, Kristian J. Hammond, et al.. (2022). Hybrid Intelligence: A Paradigm for More Responsible Practice. SSRN Electronic Journal. 6 indexed citations

Logg, Jennifer M. & Charles Dorison. (2021). Pre-registration: Weighing costs and benefits for researchers. Organizational Behavior and Human Decision Processes. 167. 18–27. 33 indexed citations

Anderson, Cameron D., et al.. (2020). The social transmission of overconfidence.. Journal of Experimental Psychology General. 150(1). 157–186. 29 indexed citations

Fast, Nathanael J., et al.. (2020). Resisting Artificial Intelligence: When Do Decision-Makers Avoid or Use Algorithmic Input?. Academy of Management Proceedings. 2020(1). 17721–17721. 1 indexed citations

Logg, Jennifer M., Julia A. Minson, & Don A. Moore. (2019). Algorithm appreciation: People prefer algorithmic to human judgment. Organizational Behavior and Human Decision Processes. 151. 90–103. 883 indexed citations breakdown →

Dai, Hengchen, et al.. (2019). The Future of Work: How People Respond to Digital Actors and Algorithms. Academy of Management Proceedings. 2019(1). 14111–14111. 2 indexed citations

Logg, Jennifer M., Uriel Haran, & Don A. Moore. (2018). Is Overconfidence a Motivated Bias? Experimental Evidence. SSRN Electronic Journal.

10.

Logg, Jennifer M., et al.. (2018). Seeker beware: The interpersonal costs of ignoring advice. Organizational Behavior and Human Decision Processes. 150. 83–100. 39 indexed citations

11.

Logg, Jennifer M., Uriel Haran, & Don A. Moore. (2018). Is overconfidence a motivated bias? Experimental evidence.. Journal of Experimental Psychology General. 147(10). 1445–1465. 46 indexed citations

12.

Logg, Jennifer M.. (2018). The Psychology of Big Data: Developing a 'Theory of Machine' to Examine Perceptions of Algorithms. SSRN Electronic Journal.

13.

Logg, Jennifer M.. (2017). Theory of Machine: When Do People Rely on Algorithms?. SSRN Electronic Journal. 10 indexed citations

14.

Logg, Jennifer M.. (2016). When do people rely on algorithms. eScholarship (California Digital Library). 9 indexed citations

15.

Tenney, Elizabeth R., Jennifer M. Logg, & Don A. Moore. (2015). (Too) optimistic about optimism: The belief that optimism improves performance.. Journal of Personality and Social Psychology. 108(3). 377–399. 63 indexed citations

16.

Arora, Poonam, Jennifer M. Logg, & Richard P. Larrick. (2015). Acting for the Greater Good: Identification with Group Determines Choices in Sequential Contribution Dilemmas. Journal of Behavioral Decision Making. 29(5). 499–510. 5 indexed citations

17.

Bohns, Vanessa K., et al.. (2011). Are social prediction errors universal? Predicting compliance with a direct request across cultures. Journal of Experimental Social Psychology. 47(3). 676–680. 29 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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