M. David Piercey

1.2k total citations
33 papers, 844 citations indexed

About

M. David Piercey is a scholar working on Accounting, General Decision Sciences and Economics and Econometrics. According to data from OpenAlex, M. David Piercey has authored 33 papers receiving a total of 844 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Accounting, 10 papers in General Decision Sciences and 7 papers in Economics and Econometrics. Recurrent topics in M. David Piercey's work include Auditing, Earnings Management, Governance (26 papers), Decision-Making and Behavioral Economics (10 papers) and Experimental Behavioral Economics Studies (6 papers). M. David Piercey is often cited by papers focused on Auditing, Earnings Management, Governance (26 papers), Decision-Making and Behavioral Economics (10 papers) and Experimental Behavioral Economics Studies (6 papers). M. David Piercey collaborates with scholars based in United States, Mexico and Canada. M. David Piercey's co-authors include Mark E. Peecher, Christopher P. Agoglia, Ryan Guggenmos, Jessen L. Hobson, Kendall Bowlin, Thomas Kida, Richard M. Tubbs, Jay S. Rich, Andrew J. Trotman and Jonathan H. Grenier and has published in prestigious journals such as The Accounting Review, Organizational Behavior and Human Decision Processes and Accounting Organizations and Society.

In The Last Decade

M. David Piercey

30 papers receiving 796 citations

Peers

M. David Piercey
Comparison fields: 5 of 52
  • Accounting 602
  • Safety Research 173
  • General Decision Sciences 171
  • Management Information Systems 141
  • Strategy and Management 137
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Citations per field, relative to M. David Piercey
M. David Piercey · 1×
Citations per year, relative to M. David Piercey
M. David Piercey · 1×

Countries citing papers authored by M. David Piercey

Since Specialization
Citations

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

Fields of papers citing papers by M. David Piercey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. David Piercey

This figure shows the co-authorship network connecting the top 25 collaborators of M. David Piercey. A scholar is included among the top collaborators of M. David Piercey 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 M. David Piercey. M. David Piercey 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
# Work Indexed citations
1 0
2 21
3 1
4 3
5 9
6 8
7 2
8 0
9 16
10 188
11
Making Sense of Seven Quandaries: Developing a Framework for Custom Contrast Analysis
1
12 29
13 42
14 32
15 14
16 2
17
The Effects of a Supervisor’s Active Intervention in Subordinates’ Judgments, Directional Goals, and Perceived Technical Knowledge Advantage on Audit Team Judgments
4
18
Motivated Reasoning and Verbal vs. Numerical Probability Assessment: Evidence from an Accounting Context
4
19 78
20 29

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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