Meng U. Taing

828 citations
9 papers · 593 · h-index 9

Impact in

Papers in

Meng U. Taing

9 papers receiving 550 citations

Peers

Meng U. Taing
Comparison fields: 5 of 88
  • Organizational Behavior and Human Resource Management 220
  • Demography 199
  • General Decision Sciences 21
  • Social Psychology 117
  • Applied Psychology 25
Replace Shefali V. Patil with:
Shefali V. Patil United States
Marion Karl Germany
Scott L. Martin United States
Nancy G. Dodd United States
Nara Youn South Korea
Shanshi Liu China
Norman T. Bruvold United States
Zhang Meng China
Yating Chuang Taiwan
Charlotta Stern Sweden
Meng U. Taing relative to Shefali V. Patil United States Shefali V. Patil's profile →
Citations per field
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Citations per year

Countries citing papers authored by Meng U. Taing

Since Specialization
Citations

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

Fields of papers citing papers by Meng U. Taing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Meng U. Taing. 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 Meng U. Taing. The network helps show where Meng U. Taing may publish in the future.

Co-authors

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

All Works

9 of 9 papers shown
#Work
1 2014168
2 2011130
3 201069
4 200867
5 200851
6 200839
7 201332
8 201420
9 201317

About Meng U. Taing

Meng U. Taing is a scholar working on Demography, Organizational Behavior and Human Resource Management, Social Psychology, Strategy and Management and Sociology and Political Science, having authored 9 papers that have together received 593 indexed citations. Recurring topics across this work include Job Satisfaction and Organizational Behavior (4 papers), Workplace Spirituality and Leadership (3 papers), Cyberloafing and Workplace Behavior (2 papers), Decision-Making and Behavioral Economics (2 papers), Organizational Leadership and Management Strategies (1 paper), Design Education and Practice (1 paper), Data Visualization and Analytics (1 paper) and Advanced Text Analysis Techniques (1 paper). The work is most often cited by research in Organizational Behavior and Human Resource Management (220 citations), Demography (199 citations), General Decision Sciences (21 citations), Social Psychology (117 citations) and Applied Psychology (25 citations). Meng U. Taing has collaborated with scholars based in United States. Frequent co-authors include Russell E. Johnson, Kevin L. Askew, Chu‐Hsiang Chang, John Buckner, Jeremy A. Bauer, Michael D. Coovert, Susan Joslyn, Emilija Djurdjevic, Christopher C. Rosen and Erin Jackson. Their work appears in journals such as Journal of Business and Psychology, Journal of Leadership & Organizational Studies, Applied Cognitive Psychology, Human Performance and Computers in Human Behavior.

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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