Tailai Wu

38 papers receiving 624 citations

Peers

Tailai Wu
Comparison fields: 5 of 107
  • Information Systems and Management 114
  • Applied Psychology 56
  • Marketing 105
  • Communication 66
  • Health 44
Replace Ashraf Sadat Ahadzadeh with:
Ashraf Sadat Ahadzadeh Malaysia
John Robert Bautista United States
Grace Johnson United States
Chen Xing China
Trent J. Spaulding United States
Yuanyuan Dang China
Gayle Prybutok United States
Ekin Seçinti United States
Junjie Zhou China
Wendy Macias United States
Tailai Wu relative to Ashraf Sadat Ahadzadeh Malaysia Ashraf Sadat Ahadzadeh's profile →
Citations per field
00.5×1.5×2.1×
Ashraf Sadat Ahadzadeh · 1×
Citations per year

Countries citing papers authored by Tailai Wu

Since Specialization
Citations

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

Fields of papers citing papers by Tailai Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Tailai Wu, 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 Tailai Wu Line = papers co-authored together Tailai Wu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016115
2 201947
3 201946
4 201845
5 201838
6 201936
7 201830
8 202229
9 201626
10 201624
11 202121
12 202120
13 202218
14 201718
15 201918
16 202017
17 201815
18 201713
19 201911
20 202210

About Tailai Wu

Tailai Wu is a scholar working on Sociology and Political Science, Information Systems and Management, Communication, Health and General Health Professions, having authored 39 papers that have together received 672 indexed citations. Recurring topics across this work include Digital Marketing and Social Media (12 papers), Technology Adoption and User Behaviour (10 papers), Knowledge Management and Sharing (5 papers), Social Media in Health Education (5 papers), Impact of Technology on Adolescents (4 papers), Customer Service Quality and Loyalty (4 papers), Mobile Health and mHealth Applications (3 papers) and Health Literacy and Information Accessibility (3 papers). The work is most often cited by research in Information Systems and Management (114 citations), Applied Psychology (56 citations), Marketing (105 citations), Communication (66 citations) and Health (44 citations). Tailai Wu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Paul Benjamin Lowry, Jun Zhang, Zhaohua Deng, Zhuo Chen, Ruoxi Wang, Donglan Zhang, Xiuyuan Gong, Zhanchun Feng, Zhiying Liu and Shangfeng Tang. Their work appears in journals such as Journal of Medical Internet Research, International Journal of Environmental Research and Public Health, Information Technology and People, Journal of the Association for Information Systems and BMC Geriatrics.

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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