Tim D. Bauer

797 citations
23 papers · 446 · h-index 9

Impact in

Papers in

    • Auditing, Earnings Management, Governance 6
    • Corporate Finance and Governance 2
    • Reinforcement Learning in Robotics 7
    • Evolutionary Algorithms and Applications 4

Tim D. Bauer

21 papers receiving 437 citations

Peers

Tim D. Bauer
Comparison fields: 5 of 52
  • Accounting 256
  • General Decision Sciences 29
  • Management Information Systems 103
  • Safety Research 67
  • Software 33
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Citations per field
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Citations per year

Countries citing papers authored by Tim D. Bauer

Since Specialization
Citations

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

Fields of papers citing papers by Tim D. Bauer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tim D. Bauer. 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 Tim D. Bauer. The network helps show where Tim D. Bauer may publish in the future.

Co-authors

The 14 scholars most cited alongside Tim D. Bauer, 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 Tim D. Bauer Line = papers co-authored together Tim D. Bauer links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014116
2 2015101
3 201975
4 202148
5 201221
6 202018
7 201112
8 201910
9 201910
10 20126
11
Improving Policy Gradient Estimates with Influence Information
20115
12 20105
13 20125
14 20233
15 20133
16 20112
17 20112
18 20121
19 20111
20 20101

About Tim D. Bauer

Tim D. Bauer is a scholar working on Accounting, Artificial Intelligence, Organizational Behavior and Human Resource Management, Information Systems and Management and Safety Research, having authored 23 papers that have together received 446 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (7 papers), Auditing, Earnings Management, Governance (6 papers), Evolutionary Algorithms and Applications (4 papers), Ethics in Business and Education (3 papers), Experimental Behavioral Economics Studies (3 papers), Software Engineering Research (3 papers), Job Satisfaction and Organizational Behavior (3 papers) and Corporate Finance and Governance (2 papers). The work is most often cited by research in Accounting (256 citations), General Decision Sciences (29 citations), Management Information Systems (103 citations), Safety Research (67 citations) and Software (33 citations). Tim D. Bauer has collaborated with scholars based in United States, Canada and Australia. Frequent co-authors include Ken T. Trotman, Kerry A. Humphreys, Cassandra Estep, Bertrand Malsch, Martin Erwig, Alan Fern, Mark E. Peecher, Alex Groce, Mohammad Amin Alipour and Kevin E. Jackson. Their work appears in journals such as Contemporary Accounting Research, The Accounting Review, Accounting Organizations and Society, Auditing A Journal of Practice & Theory and Journal of Information Systems.

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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