Jay S. Rich

781 citations
17 papers · 634 · h-index 8

Impact in

    • Decision-Making and Behavioral Economics
  • Accounting top 2%
    • Auditing, Earnings Management, Governance
    • Corporate Finance and Governance
    • Accounting Education and Careers

Papers in

Jay S. Rich

16 papers receiving 568 citations

Peers

Jay S. Rich
Comparison fields: 5 of 46
  • General Decision Sciences 134
  • Accounting 502
  • Management Information Systems 155
  • Safety Research 118
  • Information Systems and Management 53
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Citations per year

Countries citing papers authored by Jay S. Rich

Since Specialization
Citations

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

Fields of papers citing papers by Jay S. Rich

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jay S. Rich. 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 Jay S. Rich. The network helps show where Jay S. Rich may publish in the future.

Co-authors

The 20 scholars most cited alongside Jay S. Rich, 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 Jay S. Rich Line = papers co-authored together Jay S. Rich links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 1997213
2 2006151
3 201080
4 200450
5 201943
6 200433
7 200023
8 201214
9 20056
10 20105
11
The Effects of a Supervisor’s Active Intervention in Subordinates’ Judgments, Directional Goals, and Perceived Technical Knowledge Advantage on Audit Team Judgments
20104
12
Reviewers' Responses to Expectations About the Client and the Preparer
20033
13 20153
14
Cornerstones of financial and managerial accounting
20102
15 20202
16
Elaboration in Audit Financial-Statement Review: An Experimental Investigation From a Persuasion Perspective
19971
17
Cornerstones of Financial Accounting
20091

About Jay S. Rich

Jay S. Rich is a scholar working on Accounting, General Decision Sciences, Management Information Systems, Social Psychology and Strategy and Management, having authored 17 papers that have together received 634 indexed citations. Recurring topics across this work include Auditing, Earnings Management, Governance (9 papers), Decision-Making and Behavioral Economics (4 papers), Accounting and Organizational Management (3 papers), Experimental Behavioral Economics Studies (2 papers), Communication in Education and Healthcare (2 papers), Financial Reporting and Valuation Research (2 papers), Complex Systems and Decision Making (2 papers) and Psychology of Moral and Emotional Judgment (1 paper). The work is most often cited by research in General Decision Sciences (134 citations), Accounting (502 citations), Management Information Systems (155 citations), Safety Research (118 citations) and Information Systems and Management (53 citations). Jay S. Rich has collaborated with scholars based in United States and Australia. Frequent co-authors include Ira Solomon, Ken T. Trotman, T. Jeffrey Wilks, Roger D. Martin, Mark E. Peecher, Richard M. Tubbs, M. David Piercey, Brian Ballou, Christine E. Earley and Kathryn Kadous. Their work appears in journals such as The Accounting Review, Auditing A Journal of Practice & Theory, Accounting Horizons, Accounting Organizations and Society and Contemporary Accounting Research.

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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