Xingyu Wang

2.5k total citations
58 papers, 1.7k citations indexed

About

Xingyu Wang is a scholar working on Organizational Behavior and Human Resource Management, Sociology and Political Science and Social Psychology. According to data from OpenAlex, Xingyu Wang has authored 58 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Organizational Behavior and Human Resource Management, 19 papers in Sociology and Political Science and 15 papers in Social Psychology. Recurrent topics in Xingyu Wang's work include Job Satisfaction and Organizational Behavior (28 papers), Emotional Labor in Professions (10 papers) and Customer Service Quality and Loyalty (7 papers). Xingyu Wang is often cited by papers focused on Job Satisfaction and Organizational Behavior (28 papers), Emotional Labor in Professions (10 papers) and Customer Service Quality and Loyalty (7 papers). Xingyu Wang collaborates with scholars based in United States, China and Hong Kong. Xingyu Wang's co-authors include Priyanko Guchait, Ayşın Paşamehmetoğlu, Andrew McCallum, Andrés Corrada-Emmanuel, Qichang Xie, YooHee Hwang, JéAnna Abbott, Renata F. Guzzo, Xiaolin Shi and Yu Zhang and has published in prestigious journals such as Journal of Applied Psychology, Journal of Cleaner Production and The American Journal of Human Genetics.

In The Last Decade

Xingyu Wang

52 papers receiving 1.6k citations

Peers

Xingyu Wang
Comparison fields: 5 of 145
  • Organizational Behavior and Human Resource Management 528
  • Artificial Intelligence 402
  • Sociology and Political Science 343
  • Economics and Econometrics 245
  • Social Psychology 216
Replace Heungsun Hwang with:
Heungsun Hwang Canada
Daeho Lee South Korea
Hongwei Wang China
Jiayin Qi China
Mark Heitmann Germany
Jang Hyun Kim South Korea
Roman Egger Austria
Enrico Ciavolino Italy
Gregory D. Moody United States
John J. Horton United States
Heungsun Hwang Canada View profile →
Citations per field, relative to Xingyu Wang
Xingyu Wang · 1×
Citations per year, relative to Xingyu Wang
Xingyu Wang · 1×

Countries citing papers authored by Xingyu Wang

Since Specialization
Citations

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

Fields of papers citing papers by Xingyu Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xingyu Wang. 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 Xingyu Wang. The network helps show where Xingyu Wang may publish in the future.

Co-authorship network of co-authors of Xingyu Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Xingyu Wang. A scholar is included among the top collaborators of Xingyu Wang 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 Xingyu Wang. Xingyu Wang 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 1
2 0
3 1
4 3
5 5
6 20
7 4
8 3
9 15
10 1
11 1
12 1
13 1
14 27
15 96
16 40
17 21
18
Competitive multi-agent inverse reinforcement learning with sub-optimal demonstrations
12
19 33
20 77

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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