Shawn T. McClean

16 papers receiving 424 citations

Hit Papers

When Conscientious Employees Meet Intelligent Machines: A...2021202620222024202150100150

Peers

Shawn T. McClean
Comparison fields: 5 of 68
  • Organizational Behavior and Human Resource Management 205
  • Social Psychology 135
  • Sociology and Political Science 106
  • Clinical Psychology 63
  • Demography 62
Replace David S. DeGeest with:
David S. DeGeest United States
Katerina Gonzalez United States
Mingpeng Huang China
Changqing He China
Melody J. Zhang Hong Kong
Jack H. Zhang Singapore
Qiongjing Hu China
Tyler B Sabey United States
Jenny S. Wesche Germany
Shawn T. McClean relative to David S. DeGeest United States David S. DeGeest's profile →
Citations per field
00.5×3.6×
David S. DeGeest · 1×
Citations per year

Countries citing papers authored by Shawn T. McClean

Since Specialization
Citations

This map shows the geographic impact of Shawn T. McClean'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 Shawn T. McClean with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shawn T. McClean more than expected).

Fields of papers citing papers by Shawn T. McClean

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shawn T. McClean. 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 Shawn T. McClean. The network helps show where Shawn T. McClean may publish in the future.

Co-authorship network of co-authors of Shawn T. McClean

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

All Works

17 of 17 papers shown
#WorkIndexed citations
1 4
2 0
3 1
4 10
5 11
6 7
7 1
8 9
9 64
10
Stop Making Excuses for Toxic Bosses
1
11 20
12
When Conscientious Employees Meet Intelligent Machines: An Integrative Approach Inspired by Complementarity Theory and Role Theorybreakdown →
159
13 19
14 3
15
How disruptions to our morning routines harm daily productivity, and what we can do about it
1
16 26
17 99

About Shawn T. McClean

Shawn T. McClean is a scholar working on Organizational Behavior and Human Resource Management, Applied Psychology and Social Psychology, having authored 17 papers that have together received 435 indexed citations. Recurring topics across this work include Job Satisfaction and Organizational Behavior (7 papers), Behavioral Health and Interventions (3 papers) and Urban Green Space and Health (3 papers). The work is most often cited by research in Organizational Behavior and Human Resource Management (205 citations), Applied Psychology (48 citations) and Social Psychology (135 citations). Shawn T. McClean has collaborated with scholars based in United States, Singapore and United Kingdom. Frequent co-authors include Joel Koopman, Stephen H. Courtright, Russell E. Johnson, Christopher M. Barnes, Pok Man Tang, Chin Tung Stewart Ng, David De Cremer, Jack H. Zhang, Anthony C. Klotz and Julie M. McCarthy. Their work appears in journals such as Academy of Management Review, Academy of Management Journal and Journal of Applied Psychology.

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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